Microblogging is a crucial mode of online communication. However, launching a new microblogging platform remains challenging, largely due to network effects. This has resulted in entrenched (and undesirable) dominance by established players, such as X/Twitter. To overcome these network effects, Bluesky, an emerging microblogging platform, introduced starter packs — curated lists of accounts that users can follow with a single click. We ask if starter packs have the potential to tackle the critical problem of social bootstrapping in new online social networks. We assess whether starter packs have indeed been helpful in supporting Bluesky growth. Our dataset includes 25.05 × 10⁶ users and 335.42 × 10³ starter packs with 1.73 × 10⁶ members, covering the entire lifecycle of Bluesky. We study the usage of these starter packs, their ability to drive network and activity growth, and their potential downsides. We also quantify the benefits of starter packs for members and creators on user visibility and activity while identifying potential challenges. By evaluating starter packs’ effectiveness and limitations, we contribute to the broader discourse on platform growth strategies and competitive innovation in the social media landscape.

Interplanetary Filesystem (IPFS) is one of the largest peer-to-peer filesystems in operation. The network is the default storage layer for Web3 and is being presented as a solution to the centralization of the web. In this paper, we present a large-scale, multi-modal measurement study of the IPFS network. We analyze the topology, the traffic, the content providers and the entry points from the classical Internet. Our measurements show significant centralization in the IPFS network and a high share of nodes hosted in the cloud. We also shed light on the main stakeholders in the ecosystem. We discuss key challenges that might disrupt continuing efforts to decentralize the Web and highlight multiple properties that are creating pressures toward centralization.

Hybrid Information-Centric Networking (hICN) is an incrementally-deployable information-centric networking architecture that is built on top of IPv6. In hICN, application-level identifiers are directly used to route interest packets (i.e., request for content) to fetch a copy of the desired content/data from any location. However, following the Internet Protocol conventions that require storing pre-computed routing/forwarding state for all prefixes in the routers raises scalability concerns, especially at the inter-domain level. Here we consider instead the other extreme; i.e. on-demand routing computation for content name prefixes when interest packets arrive at the router. Following this approach, we propose a centralized routing service within a domain that keeps a mapping between hICN name prefixes and locators (i.e., routable addresses) to hICN routers. Once a locator is received, an hICN router forwards an interest packet towards the intended destination using segment routing. We evaluated the proposed solution through a real testbed implementation in order to demonstrate that the performance is equivalent to typical hICN forwarding, while offering a scalability solution.

Congestion control has traditionally relied on monitoring packet-level performance (e.g., latency, loss) through feedback signals propagating end-to-end together with various queue management practices (e.g., carefully setting various parameters, such as router buffer thresholds) in order to regulate traffic flow. Due to its end-to-end nature, this approach is known to transfer data according to the path’s slowest link, requiring several RTTs to transmit even a few tens of KB during slow start. In this paper, we take a radically different approach to control congestion, which obviates end-to-end performance monitoring and careful setting of network parameters. The resultingIn-Network Resource Pooling Protocol (INRPP)extends the resource pooling principle to exploit in-network resources such as router storage and unused bandwidth along alternative sub-paths. In INRPP, content caches or large (possibly bloated) router buffers are used as a place of temporary custody for incoming data packets in a store and forward manner. Data senders push data in the network and when it hits the bottleneck link, in-network caches at every hop store data in excess of the link capacity; nodes progressively move/send data (from one cache to the next) towards the destination. At the same timealternative sub-pathsare exploited to move data faster towards the destination. We demonstrate through extensive simulations that INRPP is TCP friendly, and improves flow completion time and fairness by as much as 50% compared to RCP, MPTCP and TCP, under realistic network conditions.

Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. Unlike back-end cloud systems which consolidate their resources in a centralized data center location with virtually unlimited capacity, edge-clouds comprise distributed resources at various “computation spots”, each with very limited capacity. In this article, we consider Function-as-a-Service (FaaS) edge-clouds whereapplication providersdeploy their latency-critical functions to process user requests with strict response time deadlines. In this setting, we investigate the problem ofresource provisioningandallocation. After formulating the optimal solution, we propose resource allocation and provisioning algorithms across the spectrum of fully-centralized to fully-decentralized. We evaluate the performance of these algorithms in terms of their ability to utilize CPU resources and meet request deadlines under various system parameters. Our results indicate that practical decentralized strategies, which require no coordination among computation spots, achieve performance that is close to the optimal fully-centralized strategy with coordination overheads.

Initiatives such as blockchains and decentralized storage networks are pushing for a decentralized Web3 to replace the current architecture. At the core of Web3 are network resource sharing services, which allow anyone to sell spare network capacity in return for rewards. These services require a way to establish trust, as parties are potentially malicious. This can be achieved by reputation systems. In this paper we make the case for using deep reinforcement learning in Web3 reputation calculation. More specifically, we propose a model which allows for decentralized calculation of scores with high personalization for the user.

An increasing number of Low Latency Applications (LLAs) in the entertainment, IoT, and automotive domains require response times that challenge the traditional application provisioning using distant Data Centres. The fog computing paradigm extends cloud computing at the edge and middle-tier locations of the network, providing response times an order of magnitude smaller than those that can be achieved by the current “client-to-cloud” network model. Here, we address the challenges of provisioning heavily stateful LLA in the setting where fog infrastructure consists of third-party computing resources, i.e., cloudlets, that come in the form of “data centres in the box”. We introduce FogSpot, a charging mechanism for on-path, on-demand, application provisioning. In FogSpot, cloudlets offer their resources in the form of Virtual Machines (VMs) via markets, collocated with the cloudlets, that interact with forwarded users’ application requests for VMs in real time. FogSpot associates each cloudlet with a price based on applications’ demand. The proposed mechanism’s design takes into account the characteristics of cloudlets’ resources, such as their limited elasticity, and LLAs’ attributes, like their expected QoS gain and engagement duration. Lastly, FogSpot guarantees the end users’ requests truthfulness while focusing in maximising either each cloudlet’s revenue or resource utilisation.

Traversing NAT's remains a big issue in P2P networks, and many of the previously proposed solutions are incompatible with truly decentralised emerging applications. Such applications need a decentralised NAT traversal solution without trusted centralised servers.

We propose a complete framework targeting operator-driven content caching that can be equally applied to both ISP-operated Content Delivery Networks (CDNs) and future Information-Centric Networks (ICNs). In contrast to previous proposals in this area, our solution leverages operators' control on cache placement and content routing, managing to considerably reduce network operating costs by minimizing the amount of transit traffic and balancing load among available network resources. In addition, our solution provides two key advantages over previous proposals. First, it allows for a simple computation of the optimal cache placement. Second, it provides knobs for operators to fine-tune performance. We validate our design through both analytical modeling and trace-driven simulations and show that our proposed solution achieves on average twice as many cache hits in comparison to previously proposed techniques, without increasing delivery latency. In addition, we show that the proposed framework achieves 19-33% better load balancing across links and caching nodes, being also robust to traffic spikes.

Sharding is a method for allocating data items to nodes of a distributed caching or storage system based on the result of a hash function computed on the item's identifier. It is ubiquitously used in key-value stores, CDNs and many other applications. Despite considerable work that has focused on the design and implementation of such systems, there is limited understanding of their performance in realistic operational conditions from a theoretical standpoint. In this paper we fill this gap by providing a thorough modeling of sharded caching systems, focusing particularly on load balancing and caching performance aspects. Our analysis provides important insights that can be applied to optimize the design and configuration of sharded caching systems.

Network operators have recently been developing multi-Gbps traffic monitoring tools on commodity hardware, as part of the packet-processing pipelines realizing software dataplanes. These solutions allow the execution of sophisticated per-packet monitoring using the processing power available on servers. Although advances in packet capture have enabled the interception of packets at high rates, bottlenecks can still arise in the monitoring process as a result of concurrent access to shared processor resources, variations of the traffic skew, and unbalanced packet-rate spikes. In this paper we present an adaptive monitoring framework, MONA, which is resilient to bottlenecks while maintaining the accuracy of monitoring reports above a user-specified threshold. MONA dynamically reduces the measurement task sets under adverse conditions, and reconfigures them to recover potential accuracy degradations. To quantify the monitoring accuracy at run time, MONA adopts a novel task-independent technique that generates accuracy estimates according to recently observed traffic characteristics. With a prototype implementation based on a generic packet-processing pipeline, and using well-known measurements tasks, we show that MONA achieves lossless traffic monitoring for a wide range of conditions, significantly enhances the level of monitoring accuracy, and performs adaptations at the time scale of milliseconds with limited overhead.

As end-user and edge-network devices are becoming ever more powerful, they are producing ever increasing amounts of data. Pulling all this data into the cloud for processing is impossible, not only due to its enormous volume, but also due to the stringent latency requirements of many applications. Instead, we argue that end-user and edge-network devices should collectively form edge computing swarms and complement the cloud with their storage and processing resources. This shift from centralized to edge clouds has the potential to open new horizons for application development, supporting new low-latency services and, ultimately, creating new markets for storage and processing resources. To realize this vision, we propose Named Functions at the Edge (NFE), a platform where functions can i) be identified through a routable name, ii) be requested and moved (as data objects) to process data on demand at edge nodes, iii) pull raw or anonymized data from sensors and devices, iv) securely and privately return their results to the invoker and v) compensate each party for use of their data, storage, communication or computing resources via tracking and accountability mechanisms. We use an emergency evacuation application to motivate the need for NFE and demonstrate its potential.

Native applications running over handheld devices have an irreplaceable role in users' daily activities. That said, recent studies show that users download on average zero new applications on monthly basis, which suggests that new apps can face discoverability issues. In this work, we aim for a web-based, download/installation-free access to native application features through microservices (μ Services)that are shared between user devices in a peer-to-peer (P2P)manner. Such a P2P approach is self-scalable and requires no investment for μ Service deployment, unlike mobile edge computing or Data Centre. We introduce DEEM, a DEvice Edge Market design that enables device-hosted μServices to end-users. In DEEM, μ Service-based markets act as rendezvous points between available μ Service instances and clients. DEEM ensures the i) assignment of instances to the users that value them the most, in terms of QoS gain, and ii) devices' income maximisation. Our evaluation on synthetic settings demonstrates DEEM's capability in exploiting the pool of device instances for improving the application QoS in terms of latency.

Traditional network functions (NFs) such as firewalls are implemented in costly dedicated hardware. By decoupling NFs from physical devices, network function virtualization enables virtual network functions (VNF) to run in virtual machines (VMs). However, VNFs are vulnerable to various faults such as software and hardware failures. To enhance VNF fault tolerance, the deployment of backup VNFs in stand-by VM instances is necessary. In case of stateful VNFs, stand-by instances require constant state updates from active instances during its operation. This will guarantee a correct and seamless handover from failed instances to stand-by instances after failures. Nevertheless, such state updates to stand-by instances could consume significant network bandwidth resources and lead to potential admission failures for VNF requests. In this paper, we study the fault-tolerant VNF placement problem with the optimization objective of admitting as many requests as possible. In particular, the VNF placement of active/stand-by instances, the request routing paths to active instances, and state transfer paths to stand-by instances are jointly considered. We devise an efficient heuristic algorithm to solve this problem, and propose a bicriteria approximation algorithm with performance guarantees for a special case of the problem. Simulations with realistic settings show that our algorithms can significantly improve the request admission rate compared to conventional approaches.

The dominant application in today's Internet is content streaming, which is increasingly relying on caches to meet the stringent conditions on the latency between content servers and end-users. These systems routinely face the challenges of limited bandwidth capacities and network server failures, which degrade caching performance. In this paper, we study the problem of optimally allocating content over a resilient caching network, in which each cache may fail under some situations. Given content request rates and multiple routing paths, we formulate an optimization problem to maximize the expected caching gain, i.e., the reduction of latency due to intermediate caching. The offline version of this problem is NP-hard. We first propose a centralized, offline algorithm and show that a solution with (1-1/e) approximation ratio to the optimal can be constructed. We then propose a distributed ascent algorithm based on the concave relaxation of the expected gain. Informed by the results of our analysis, we finally propose a distributed resilient caching algorithm (DR-Cache) that is simple and adaptive to network failures. We show numerically that DR-Cache significantly outperforms other candidate algorithms under synthetic requests, as well as real world traces over a class of network topologies.

Cloud computing has been tremendously successful in providing a commercial infrastructure for hosting computationally intensive applications. Nevertheless, an increasing number of Low Latency Applications (LLAs) notably in the entertainment, IoT, and automative domains require response times much smaller than the supported ones by the typical “client-to-cloud” network model. Cloudlets have been introduced as “data centres in a box”, for bringing computing resources “closer” to the end users. As a result, LLAs can take advantage of cloudlets to improve their Quality-of-Service (QoS) by reducing the underlying response times between their users and application instances' location. In this work, we study the emerging market of stateful LLAs' provisioning over geo-distributed third-party cloudlets. We assume that cloudlets offer their resources in the form of Virtual Machines (VMs) via collocated markets. Forwarding requests for LLAs interact with cloudlet markets for performing on-path and on-demand resource provisioning. We introduce a pricing scheme where users pay a fixed price for each time unit of their engagement to an LLA instance. Our evaluation on realistic topologies and application requests demonstrate the merits of on-demand provisioning when accompanied by a pay-as-you-go pricing scheme.

New and emerging applications in the entertainment (e.g., Virtual/Augmented Reality), IoT and automotive domains will soon demand response times an order of magnitude smaller than can be achieved by the current “client-to-cloud” network model. Edge-and Fog-computing have been proposed as the promise to deal with such extremely latency-sensitive applications. According to Edge-/Fog-Computing, computing resources are available at the edge of the network for applications to run their virtualised instances. We assume a distributed computing environment, where In-Network Computing Providers (IN CPs) deploy and lease edge resources, while Application Service Providers (AppSPs) have the opportunity to rent those resources to meet their application's latency demands. We build an auction-based resource allocation and provisioning mechanism which produces a map of application instances in the edge computing infrastructure (hence, acronymed Edge-MAP). Edge-MAP takes into account users' mobility (i.e., users connecting to different cell stations over time) and the limited computing resources available in edge micro-clouds to allocate resources to bidding applications. On the micro-level, Edge-MAP relies on Vickrey-English-Dutch (VED) auctions to perform robust resource allocation, while on the macro-level it fosters competition among neighbouring IN CPs. In contrast to related studies in the area, Edge-MAP can scale to any number of applications, adapt to dynamic network conditions rapidly and reallocate resources in polynomial time. Our evaluation demonstrates Edge-MAP's capability of taking into account the inherent challenges of the provisioning problem we consider.

We argue that data communications in dynamic and potentially fragmented networks should not and cannot rely on network-centric resilience schemes, as is the case in today's networks, but should take advantage of techniques that focus on information-centric resilience. We make the case that management and control in disruptive environments should take advantage of information-centricity, rather than focus on node-oriented path recovery routing. This is also essential in the information-centric networking (ICN) paradigm, which is by nature oblivious to network locations. In this context, we build on ICN and enhance the named data networking (NDN) architecture with extra functionality in order to make it resilient to network failures. We introduce an extra interest management routing table, which we call the “satisfied interest table” (SIT) and which points to the direction of already satisfied interests. This way, upon failure of links/nodes toward the content origin, the SIT table can redirect interests toward caches and end-users that have recently received the requested content. Our extensive performance evaluation shows that our simple, yet efficient information resilience scheme can serve most requests made after disruptive effects, e.g., natural disasters, where users are interested in latest updates, dissemination of warnings from first responders and evacuation plans. More generally, we believe that our proposed approach should become part of the main NDN architecture as it can support service resilience in the case of network failures.

The software-defined networking (SDN) paradigm can allow network management solutions to automatically and frequently reconfigure network resources. When developing SDN-based management architectures, it is of paramount importance to design a monitoring system that can provide timely and consistent updates to heterogeneous management applications. To support such applications operating with low latency requirements, the monitoring system should scale with increasing network size and provide precise network views with minimum overhead on the available resources. In this paper, we present a novel, self-adaptive, decentralized framework for resource monitoring in SDN. Our framework enables accurate statistics to be collected with limited burden on the network resources. This is realized through a self-tuning, adaptive monitoring mechanism that automatically adjusts its settings based on the traffic dynamics. We evaluate our proposal based on a realistic use case scenario, where a content distribution service and an on-demand gaming platform are deployed within an ISP network. The results show that reduced monitoring latencies are obtained with the proposed framework, thus enabling shorter reconfiguration control loops. In addition, the proposed adaptive monitoring method achieves significant gain in terms of monitoring overhead, while preserving the performance of the services considered.

Mobile edge-cloud (MEC) aims to support low latency mobile services by bringing remote cloud services nearer to mobile users. However, in order to deal with dynamic workloads, MEC is deployed in a large number of fixed-location micro-clouds, leading to resource wastage during stable/low workload periods. Limiting the number of micro-clouds improves resource utilization and saves operational costs, but faces service performance degradations due to insufficient physical capacity during peak time from nearby micro-clouds. To efficiently support services with low latency requirement under varying workload conditions, we adopt the emerging network function virtualization (NFV)-enabled MEC, which offers new flexibility in hosting MEC services in any virtualized network node, e.g., access points, routers, etc. This flexibility overcomes the limitations imposed by fixed-location solutions, providing new freedom in terms of MEC service-hosting locations. In this paper, we address the questions on where and when to allocate resources as well as how many resources to be allocated among NFV-enabled MECs, such that both the low latency requirements of mobile services and MEC cost efficiency are achieved. We propose a dynamic resource allocation framework that consists of a fast heuristic-based incremental allocation mechanism that dynamically performs resource allocation and a reoptimization algorithm that periodically adjusts allocation to maintain a near-optimal MEC operational cost over time. We show through extensive simulations that our flexible framework always manages to allocate sufficient resources in time to guarantee continuous satisfaction of applications' low latency requirements. At the same time, our proposal saves up to 33% of cost in comparison to existing fixed-location MEC solutions.

Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. ISPs have the opportunity to deploy private edge-clouds in their infrastructure to generate additional revenue by providing ultra-low latency applications to local users. We envision a rapid increase in the number of such applications for “edge” networks in the near future with virtual/augmented reality (VR/AR), networked gaming, wearable cognitive assistance, autonomous driving and IoT analytics having already been proposed for edge- clouds instead of the central clouds to improve performance. This raises new challenges as the complexity of the resource allocation problem for multiple services with latency deadlines (i.e., which service to place at which node of the edge-cloud in order to satisfy the latency constraints) becomes significant. In this paper, we propose a set of practical, uncoordinated strategies for service placement in edge-clouds. Through extensive simulations using both synthetic and real-world trace data, we demonstrate that uncoordinated strategies can perform comparatively well with the optimal placement solution, which satisfies the maximum amount of user requests.

Network operators have recently been developing multi-Gbps traffic monitoring tools that execute on commodity hardware and are part of the packet-processing pipelines realizing software dataplanes. These solutions allow sophisticated tasks to be performed on a per-packet basis, without relying on sampling or passive trace analysis, by leveraging the processing power available on servers. Although advances in packet capture have enabled intercepting packets from network cards at high rates, bottlenecks can still arise in the monitoring process as a result of concurrent access to shared processor resources, variations of the traffic skew, and unbalanced packet-rate spikes. In this paper we present an adaptive traffic monitoring approach that copes with emerging bottlenecks by timely detecting changes in the operational conditions and reconfiguring monitoring-related operations for subsets of traffic flows. Our solution performs responsive adaptations at the time scale of milliseconds and does not require a significant amount of resources. To demonstrate the capabilities of our approach we implemented it as part of a generic packet-processing pipeline and show that lossless traffic monitoring can be achieved for a wide range of conditions.

The Software-Defined Networking (SDN) paradigm can allow network management solutions to automatically and frequently reconfigure network resources. When developing SDN-based management architectures, it is of paramount importance to design a monitoring system that can provide frequent and consistent updates to heterogeneous management applications. For the monitoring functionality to scale according to the requirements of large-scale networks a distributed monitoring approach is required. In this paper we present a decentralized approach for resource monitoring in SDN, which is designed to support a wide range of measurement tasks and requirements in terms of monitoring rates and information granularity levels. Our solution leverages effective processing of the monitoring requests to reduce the consumption of limited resources, such as the control plane bandwidth of OpenFlow switches. To demonstrate the benefits of the proposed approach, our evaluation is based on a realistic and demanding use case, where a distributed management application coordinates a content distribution service in an ISP network.

Recent approaches have proposed to empower Internet Service Providers (ISPs) with caching capabilities that can allow them to implement their own cache management strategies and as such have better control over the utilization of their resources. In this demo paper, we present CacheMAsT (Cache Management Analysis and Visualization Tool), a decision support tool to visualize the configuration and performance of in-network cache management approaches. CacheMAsT is aimed at assisting researchers and engineers in analyzing and evaluating the different factors that can affect the performance of a cache management strategy and ultimately decide on the optimal approach to apply.

The vast majority of mobile data transfers today follow the traditional client-server model. Although in the fixed network P2P approaches have been exploited and shown to be very efficient, in the mobile domain there has been limited attempt to leverage on P2P (D2D) for large-scale content distribution (i.e., not DTN-like, point-to-point message transfers). In this paper, we explore the potential of a user-operated, smartphone-centric content distribution model for smartphone applications. In particular, we assume source nodes that are updated directly from the content provider (e.g., BBC, CNN), whenever updates are available; destination nodes are then directly updated by source nodes in a D2D manner. We leverage on sophisticated information-aware and application-centric connectivity techniques to distribute content between mobile devices in densely-populated urban environments. Our target is to investigate the feasibility of an opportunistic content distribution network in an attempt to achieve widespread distribution of heavy content (e.g., video files) to the majority of the destination nodes. We propose ubiCDN as a ubiquitous, user-operated and distributed CDN for mobile applications.

The management of network infrastructures has become increasingly complex over time, which is mainly attributed to the introduction of new functionality to support emerging services and applications. To address this important issue, research efforts in the last few years focused on developing software-defined networking solutions. While initial work proposed centralized architectures, their scalability limitations have led researchers to investigate a distributed control plane. Controller placement algorithms and mechanisms for building a logically centralized network view are some examples of challenges addressed in this context. A critical issue that requires specific attention concerns the communication between distributed entities involved in decision-making processes. To this end, we propose SigMA, a signaling framework that supports communication between the different entities of a decentralized management and control system. We also define the communication primitives and interfaces involved in such a decentralized environment. The benefits of SigMA are illustrated through three realistic network resource management use cases with different communication requirements. Based on simulation, we demonstrate the flexibility and extensibility of our solution in satisfying these requirements, thus effectively supporting advanced decentralized decision-making processes.

Conventional epidemic models assume omni-directional contact-based infection. This strongly associates the epidemic spreading process with node degrees. The role of the infection transmission medium is often neglected. In real-world networks, however, the infectious agent as the physical contagion medium usually flows from one node to another via specific directed routes (path-based infection). Here, we use continuous-time Markov chain analysis to model the influence of the infectious agent and routing paths on the spreading behavior by taking into account the state transitions of each node individually, rather than the mean aggregated behavior of all nodes. By applying a mean field approximation, the analysis complexity of the path-based infection mechanics is reduced from exponential to polynomial. We show that the structure of the topology plays a secondary role in determining the size of the epidemic. Instead, it is the routing algorithm and traffic intensity that determine the survivability and the steady-state of the epidemic. We define an infection characterization matrix that encodes both the routing and the traffic information. Based on this, we derive the critical path-based epidemic threshold below which the epidemic will die off, as well as conditional bounds of this threshold which network operators may use to promote/suppress path-based spreading in their networks. Finally, besides artificially generated random and scale-free graphs, we also use real-world networks and traffic, as case studies, in order to compare the behaviors of contact- and path-based epidemics. Our results further corroborate the recent empirical observations that epidemics in communication networks are highly persistent.

Sharding is a method for allocating data items to nodes of a distributed caching or storage system based on the result of a hash function computed on the item identifier. It is ubiquitously used in key-value stores, CDNs and many other applications. Despite considerable work has focused on the design and the implementation of such systems, there is limited understanding of their performance in realistic operational conditions from a theoretical standpoint. In this paper we fill this gap by providing a thorough modeling of sharded caching systems, focusing particularly on load balancing and caching performance aspects. Our analysis provides important insights that can be applied to optimize the design and configuration of sharded caching systems.

Recent research in Information-Centric Networks has considered various approaches for discovering content in the cache-enabled nodes of the network. Such approaches include scoped flooding and deploying a control plane protocol to disseminate the cache contents in the network, to name a few. In this work, we consider an opportunistic approach that uses trails left behind by data packets from the content origin to the sources in order to discover off-path cached content. We evaluate our approach using an ISP topology for various system parameters. We propose two new forwarding strategies built on top of our approach. Our results indicate that the opportunistic discovery mechanism can significantly increase cache hit rate compared to NDN's default forwarding strategy, while limiting the overhead at acceptable levels.

The management of network infrastructures has become increasingly complex over time, which is mainly attributed to the introduction of new functionality to support emerging services and applications. To address this important issue, research efforts in the last few years focused on developing Software-Defined Networking solutions. While initial work proposed centralized architectures, their scalability limitations have led researchers to investigate a distributed control plane, with controller placement algorithms and mechanisms for building a logically centralized network view, being examples of challenges addressed. A critical issue that has not been adequately addressed concerns the communication between distributed decision-making entities to ensure configuration consistency. To this end, this paper proposes a signaling framework that can allow the exchange of information in distributed management and control scenarios. The benefits of the proposed framework are illustrated through a realistic network resource management use case. Based on simulation, we demonstrate the flexibility and extensibility of our solution in meeting the requirements of distributed decision-making processes.

Content delivery networks (CDNs) have been the prevalent method for the efficient delivery of content across the Internet. Management operations performed by CDNs are usually applied only based on limited information about Internet Service Provider (ISP) networks, which can have a negative impact on the utilization of ISP resources. To overcome these issues, previous research efforts have been investigating ISP-operated content delivery services, by which an ISP can deploy its own in-network caching infrastructure and implement its own cache management strategies. In this paper, we extend our previous work on ISP-operated content distribution and develop a novel scalable and efficient distributed approach to control the placement of content in the available caching points. The proposed approach relies on parallelizing the decision-making process and the use of network partitioning to cluster the distributed decision-making points, which enables fast reconfiguration and limits the volume of information required to take reconfiguration decisions. We evaluate the performance of our approach based on a wide range of parameters. The results demonstrate that the proposed solution can outperform previous approaches in terms of management overhead and complexity while offering similar network and caching performance.

Traffic engineering (TE) functionality aims to control and fine-tune the routing configuration and bandwidth allocation in order to optimize the use of network resources and avoid the build-up of congestion. The performance of a given TE scheme is, however, strongly influenced by the degree of flexibility offered in distributing the traffic load. Multipath routing coupled with arbitrary traffic splitting are two essential ingredients for achieving the desired flexibility. Current proposals for multipath routing in OpenFlow have mostly focused on equal splitting solutions, which impose limitations in terms of the level of control that can be achieved. In this paper, we investigate a new approach, which exploits the properties of bit-masking operations to enable flexible TE in OpenFlow networks. The proposed solution relies on the matching entry feature and the multiple table pipeline capability of OpenFlow, and as such, is in line with the current standard. Based on empirical evaluation, we illustrate the influence of the considered masking parameters and how these can be configured to achieve the desired traffic splitting ratios. The results demonstrate that our solution can achieve a similar level of splitting accuracy as the one obtained with a hash-based approach. However, in contrast to current proposals, it does not require complex extensions to the OpenFlow protocol and can be easily implemented in an OpenFlow environment.

In order to support reactive and adaptive operations, Software-Defined Networking (SDN)-based management and control frameworks call for decentralized solutions. A key challenge to consider when deploying such solutions is to decide on the degree of distribution of the management and control functionality. In this paper, we develop an approach to determine the allocation of management and control entities by designing two algorithms to compute their placement. The algorithms rely on a set of input parameters which can be tuned to take into account the requirements of both the network infrastructure and the management applications to execute in the network. We evaluate the influence of these parameters on the configuration of the resulting management and control planes based on real network topologies and provide guidelines regarding the settings of the proposed algorithms.

On behalf of the Organizing and Technical Program Committees, we are pleased to welcome you to the inaugural conference on IEEE Network Softwarization (NetSoft 2015), in London, UK, April 13–17, 2015.

Name resolution is at the heart of Information-Centric Networking (ICN), where names are used to both identify information and/or services, and to guide routing and forwarding inside the network. The ICN focus on information, rather than hosts, raises significant concerns regarding the scalability of the required Name Resolution System (NRS), especially when considering global scale, inter-domain deployments. In the route-by-name approach to NRS construction, name resolution and the corresponding state follow the routing infrastructure of the underlying inter-domain network. The scalability of the resulting NRS is therefore strongly related to the topological and routing characteristics of the network. However, past work has largely neglected this aspect. In this paper, we present a detailed investigation and comparison of the scalability properties of two route-by-name inter-domain NRS designs, namely, DONA and CURLING. Based on both real, full-scale inter-domain topology traces and synthetic, scaled-down topologies, our work quantifies a series of important scalability-related performance aspects, including the distribution of name-resolution state across the Internet topology and the associated processing and signaling overheads. We show that by avoiding DONA's exchange of state across peering links, CURLING results in deployment costs proportional to the total number of downstream customers of each Autonomous System. This translates to a 62-fold global state size reduction, at the expense of a 2.78-fold increase in lookup processing load, making CURLING a feasible approach to ICN name resolution.

We investigate an information-resilience scheme in the context of Content-Centric Networks (CCN) for the retrieval of content in disruptive, fragmented networks cases. To resolve and fetch content when the origin is not available due to fragmentation, we exploit content cached both in in-network caches and in end-users' devices. Initially, we present the required modifications in the CCN architecture to support the proposed resilience scheme. We also present the family of policies that enable the retrieval of cached content and we derive an analytical expression/lower bound of the probability that an information item will disappear from the network (be absorbed) and the time to absorption when the origin of the item is not reachable. Extensive simulations indicate that the proposed resilience scheme is a valid tool for the retrieval of cached content in disruptive scenarios, since it allows the retrieval of content for a long period after the fragmentation of the network and the “disappearance” of the content origin.

The heterogeneous nature of the applications, technologies and equipment that today's networks have to support has made the management of such infrastructures a complex task. The Software-Defined Networking (SDN) paradigm has emerged as a promising solution to reduce this complexity through the creation of a unified control plane independent of specific vendor equipment. However, designing a SDN-based solution for network resource management raises several challenges as it should exhibit flexibility, scalability and adaptability. In this paper, we present a new SDN-based management and control framework for fixed backbone networks, which provides support for both static and dynamic resource management applications. The framework consists of three layers which interact with each other through a set of interfaces. We develop a placement algorithm to determine the allocation of managers and controllers in the proposed distributed management and control layer. We then show how this layer can satisfy the requirements of two specific applications for adaptive load-balancing and energy management purposes.

We question the widely adopted view of in-network caches acting as temporary storage for the most popular content in Information-Centric Networks (ICN). Instead, we propose that in-network storage is used as a place of temporary custody for incoming content in a store and forward manner. Given this functionality of in-network storage, senders push content into the network in an open-loop manner to take advantage of underutilised links. When content hits the bottleneck link it gets re-routed through alternative uncongested paths. If alternative paths do not exist, incoming content is temporarily stored in in-network caches, while the system enters a closed-loop, back-pressure mode of operation to avoid congestive collapse.

TCP remains the dominant transport protocol for Internet traffic, but the preponderance of its congestion control mechanisms in determining flow throughput is often disputed. This paper analyzes the extent to which network, host and application settings define flow throughput over time and across autonomous systems. Drawing from a longitudinal study spanning five years of passive traces collected from a single transit link, our results show that continuing OS upgrades have reduced the influence of host limitations owing both to windowscale deployment, which by 2011 covered 80% of inbound traffic, and increased socket buffer sizes. On the other hand, we show that for this data set, approximately half of all inbound traffic remains throttled by constraints beyond network capacity, challenging the traditional model of congestion control in TCP traffic as governed primarily by loss and delay.

Existing methods for traffic resilience at the network and transport layers typically work in isolation, often resorting to inference in fault detection and recovery respectively. This both duplicates functionality across layers, eroding efficiency, and leads to protracted recovery cycles, affecting responsiveness. Such misalignment is particularly at odds with the unprecedented concentration of traffic in data-centers, in which network and hosts are managed in unison. This paper advocates instead a cross-layer approach to traffic resilience. The proposed architecture, INFLEX, builds on the abstractions provided by software-defined networking (SDN) to maintain multiple virtual forwarding planes which the network assigns to flows. In case of path failure, transport protocols pro-actively request to switch plane in a manner which is unilaterally deployable by an edge domain, providing scalable end-to-end forwarding path resilience.

Centralized and offline network management functionality, traditionally deployed by operators, cannot easily deal with the traffic patterns of emerging services, which are becoming more dynamic and unpredictable. As such, decentralized solutions that are flexible and adaptive to traffic and network dynamics are of paramount importance. To this end, we have been developing an in-network management approach in which an intelligent substrate allows the dynamic reconfiguration of resources according to network conditions. The set of nodes forming this logical structure are able to communicate with each other to coordinate their decisions. While in previous work we investigated the use of full-mesh and ring structures to connect the substrate nodes, we consider here a hybrid approach that combines the benefits of the other two. We describe algorithms that can be practically used to compute this hybrid structure and that take into account important criteria such as minimizing the latency and the communication overhead among the substrate nodes. We evaluate the impact of key parameters associated with the construction process.

Inspired by the proliferation of content-centric applications in the Internet, Information-Centric Networking (ICN) has emerged as a promising networking paradigm. Focusing on the delivery of content instead of the pairwise communication between end-hosts, ICN inherently supports location-independent content/information distribution, through the means of in-network caching and multicast; as well as mobile computing. However, so far the vast majority of ICN research efforts have mostly focused on the design of sound and scalable architectures and protocols for the current Internet application landscape. In this paper, we revisit ICN in the context of a radically different application environment of smart grids and in particular, the case of smart charging of electric vehicles. Based on a thorough description of the currently forming application environment in the Netherlands, we highlight the inefficiencies resulting from a host-centric model. We then show how ICN can address these limitations and ultimately support quality and security in such application environment. Besides qualitative benefits, our preliminary analysis also demonstrates that ICN can substantially reduce communication and security complexity, thus fostering the development and widespread adoption of the smart charging application.

The proposed shift from host-centric to information-centric networking (ICN) has triggered extensive research in the area of content naming. Efforts have so far focused on the scalability and security properties that can make content objects routable and self-certifying. In this paper, we argue that the information that is exposed through explicitly naming content objects has been overlooked, although several operational and performance issues depend on the information that a name holds. We therefore revisit content naming design decisions taking into account information exposure and deployability of the ICN paradigm.

We introduce the concept of resource management for in-network caching environments. We argue that in Information-Centric Networking environments, deterministically caching content messages at predefined places along the content delivery path results in unfair and inefficient content multiplexing between different content flows, as well as in significant caching redundancy. Instead, allocating resources along the path according to content flow characteristics results in better use of network resources and therefore, higher overall performance. The design principles of our proposed in-network caching scheme, which we call ProbCache, target these two outcomes, namely reduction of caching redundancy and fair content flow multiplexing along the delivery path. In particular, ProbCache approximates the caching capability of a path and caches contents probabilistically to: 1) leave caching space for other flows sharing (part of) the same path, and 2) fairly multiplex contents in caches along the path from the server to the client. We elaborate on the content multiplexing fairness of ProbCache and find that it sometimes behaves in favor of content flows connected far away from the source, that is, it gives higher priority to flows travelling longer paths, leaving little space to shorter-path flows. We introduce an enhanced version of the main algorithm that guarantees fair behavior to all participating content flows. We evaluate the proposed schemes in both homogeneous and heterogeneous cache size environments and formulate a framework for resource allocation in in-network caching environments. The proposed probabilistic approach to in-network caching exhibits ideal performance both in terms of network resource utilization and in terms of resource allocation fairness among competing content flows. Finally, and in contrast to the expected behavior, we find that the efficient design of ProbCache results in fast convergence to caching of popular content items.

Management operations performed by Content Delivery Network (CDN) providers consist mainly in controlling the placement of contents at different storage locations and deciding where to serve client requests from. Configuration decisions are usually taken by using only limited information about the carrier networks, and this can adversely affect network usage. In this work we propose an approach by which ISPs can have more control over their resources. This involves the deployment of caching points within their network, which can allow them to implement their own content placement strategies. The work presented in this paper investigates lightweight strategies that can be used by the ISPs to manage the placement of contents in the various network caching locations according to user demand characteristics. The proposed strategies differ in terms of the volume and nature of the information required to determine the new caching configurations. We evaluate the performance of the proposed strategies, in terms of network resource utilization, based on a wide range of user demand profiles and we compare the obtained performance according to metrics we define to characterize the demand. The results demonstrate that the proposed metrics can provide useful indications regarding the performance one strategy can achieve over another and, as such, can be used by the ISP to improve the utilization of network resources.

Content Centric Networking (CCN) is a recently proposed information-centric Internet architecture in which the main network abstraction is represented by location-agnostic content identifiers instead of node identifiers. In CCN each content object is divided into packet-size chunks. When a content object is transferred, routers on the path can cache single chunks which they can use to serve subsequent requests from other users. Since content chunks in CCN may be retrieved from a number of different nodes/caches, implicit-feedback transport protocols will not be able to work efficiently, because it is not possible to set an appropriate timeout value based on RTT estimations given that the data source may change frequently during a flow. In order to address this problem, we propose in this paper a scalable, implicit-feedback congestion control protocol, capable of coping with RTT unpredictability using a novel anticipated interests mechanism to predict the location of chunks before they are actually served. Our evaluation shows that our protocol outperforms similar receiver-driven protocols, in particular when content chunks are scattered across network paths due to reduced cache sizes, long-tail content popularity distribution or the adoption of specific caching policies.

This paper addresses the problem of provisioning management/monitoring nodes within highly dynamic network environments, particularly virtual networks. In a network, where nodes and links may be spontaneously created and destroyed (perhaps rapidly) there is a need for stable and responsive management and monitoring, which does not create a large load (in terms of traffic or processing) for the system. A subset of nodes has to be chosen for management/monitoring, each of which will manage a subset of the nodes in the network. A new, simple, and locally optimal greedy algorithm called Pressure is provided for choice of node position to minimize traffic. This algorithm is combined with a system for predicting the lifespan of nodes, and a tunable parameter is also given so that a system operator could express a preference for elected nodes to be chosen to reduce traffic, to be “stable,” or some compromise between these positions. The combined algorithm called PressureTime is lightweight and could be run in a distributed manner. The resulting algorithms are tested both in simulation and in a testbed environment of virtual routers. They perform well, both at reducing traffic and at choosing long lifespan nodes.

In order to meet the requirements of emerging demanding services, network resource management functionality that is decentralized, flexible and adaptive to traffic and network dynamics is of paramount importance. In this paper we describe the main mechanisms of DACoRM, a new intra-domain adaptive resource management approach for IP networks. Based on path diversity provided by multi-topology routing, our approach controls the distribution of traffic load in the network in an adaptive manner through periodical re-configurations that uses real-time monitoring information. The re-configuration actions performed are decided in a coordinated fashion between a set of source nodes that form an in-network overlay. We evaluate the overall performance of our approach using realistic network topologies. Results show that near-optimal network performance in terms of resource utilization can be achieved in scalable manner.

Fast reroute (FRR) techniques have been designed and standardised in recent years for supporting sub-50-millisecond failure recovery in operational ISP networks. On the other hand, if the provisioning of FRR protection paths does not take into account traffic engineering (TE) requirements, customer traffic may still get disrupted due to post-failure traffic congestion. Such a situation could be more severe in operational networks with highly dynamic traffic patterns. In this paper we propose a distributed technique that enables adaptive control of FRR protection paths against dynamic traffic conditions, resulting in self-optimisation in addition to the self-healing capability. Our approach is based on the Loop-free Alternates (LFA) mechanism that allows non-deterministic provisioning of protection paths. The idea is for repairing routers to periodically re-compute LFA alternative next-hops using a lightweight algorithm for achieving and maintaining optimised post-failure traffic distribution in dynamic network environments. Our experiments based on a real operational network topology and traffic traces across 24 hours have shown that such an approach is able to significantly enhance relevant network performance compared to both TE-agnostic and static TE-aware FRR solutions.

Information-Centric Networking (ICN), also referred to as content-centric, content-aware or data-oriented networking is seen as an emerging paradigm that tries to re-focus communications, centering on content access rather than on host-to-host interaction as is the case today. The proliferation of user-generated content and the fact that the vast majority of interactions over the Internet concern media content access has led researchers to think of new communication models in which information/content comes on center stage and is accessed in a location-independent fashion; in addition, the underlying network is aware of the content characteristics and optimizes delivery accordingly. The resulting communications paradigm is receiver-driven, with “time-phased” multicasting and in-network caching being the norm. The network infrastructure becomes more intelligent, with application logic potentially executing within the network in order to support demanding media applications that are not possible today. Summary form only given. This presentation will start with an overview of information-centric networking; it will present the state-of-the-art in the relevant research activities and will consider the current state and key challenges. The management challenges of the expected fluid and more dynamic network infrastructure will also be specially considered.

The recently proposed Application Layer Traffic Optimization (ALTO) framework has opened up a new dimension for Internet traffic management that is complementary to the traditional application-agnostic traffic engineering (AATE) solutions currently employed by ISPs. In this paper, we investigate how ALTO-assisted Peer-to-Peer (P2P) traffic management functions interact with the underlying AATE operations, given that there may exist different application-layer policies in the P2P overlay. By considering specific P2P peer selection behaviors on top of a traffic-engineered ISP network, we conduct a performance analysis on how the application and network-layer respective performance is influenced by different policies at the P2P side. Our empirical study offers significant insight for the future design and analysis of cross-layer network engineering approaches that involve multiple autonomous optimization entities with both consistent and non-consistent policies.

Emerging Peer-to-Peer (P2P) technologies have enabled various types of content to be efficiently distributed over the Internet. Most P2P systems adopt selfish peer selection schemes in the application layer that in some sense optimize the user quality of experience. On the network side, traffic engineering (TE) is deployed by ISPs in order to achieve overall efficient network resource utilization. These TE operations are typically performed without distinguishing between P2P flows and other types of traffic. Due to inconsistent or even conflicting objectives from the perspectives of P2P overlay and network-level TE, the interactions between the two and their impact on the performance for each is likely to be non-optimal, and also has not yet been investigated in detail. In this paper we study such non-cooperative interactions by modeling best-reply dynamics, in which the P2P overlay and network-level TE optimize their own strategies based on the decision of the other player in the previous round. According to our simulations results based on data from the ABILENE network, P2P overlays exhibit strong resilience to adverse TE operations in maintaining end-to-end performance at the application layer. In addition, we show that network-level TE may suffer from performance deterioration caused by greedy peer (re-)selection behavior in reacting to previous TE adjustments.

There has recently been an increasing research interest in network management infrastructures that autonomously adapt to the dynamics of the environment. In this paper, we present an information management platform, called the Information Management Overlay (IMO), which is an infrastructure that regulates information flow based on the properties and the state of the network environment. We discuss the design, implementation and optimization issues of this platform and we investigate experimentally how the IMO can adapt to different settings and optimization requirements.

Several intra- and inter-domain quality of service (QoS) provisioning mechanisms for IP networks have been researched and developed using Differentiated Services (DiffServ) technology. However, the incremental efforts needed to manage DiffServ networks from a business-oriented viewpoint have received relatively little attention. This paper addresses this gap and presents a framework for achieving business-driven QoS provisioning in DiffServ over MPLS networks. We provide a rich model of SLA and business indicators as well as reasonable mapping functions that define, with key degrees of importance, the impact of business indicators over service management policies. Business and service indicators are used to control static and dynamic admission of services. The paper advances the state of the art by considering the influence of business-level objectives on the policy refinement process. We evaluate and discuss the effectiveness of our approach through a simulation environment that we developed over OPNET.

As a scalable paradigm for content distribution at Internet-wide scale, Peer-to-Peer (P2P) technologies have enabled a variety of networked services, such as distributed file-sharing and live video streaming. Most existing P2P systems employ non-intelligent peer selection algorithms for content swarming which greedily consume Internet bandwidth resources. As a result, Internet service providers (ISPs) need some efficient solutions for managing P2P traffic within their own networks. A common practice today is to block or shape P2P traffic in order to conserve bandwidth resources for carrying standard traffic from which revenue can be generated. In this paper, instead of looking at simple time-driven blocking/limiting approaches, we investigate how such types of limiting behaviors can be more gracefully performed by the ISP by taking into account the dynamics of both P2P traffic and of standard Internet traffic. Specifically, our approach is to adaptively limit excessive P2P traffic on critical network links that are prone to congestion, based on periodical link load/utilization measurements by the ISP. The ultimate objective is to guarantee non-P2P service capability while trying to accommodate as much P2P traffic as possible based on the available bandwidth resources. This approach can be regarded as a complementary solution to the recently proposed collaboration-based P2P paradigms such as P4P. Simulation results show that our approach not only eliminates performance degradation of non-P2P services that are caused by overwhelming P2P traffic, but also accommodates P2P traffic efficiently in both existing and future collaboration-based P2P network scenarios.

The nine papers in this special issue focus on recent advances in autonomic communications. This issue addresses four areas in which autonomics play a central role: network architectures, traffic management, monitoring, and resource management.

We present an efficient multi-plane based fast network failure recovery scheme which can be realized using the recently proposed multi-path enabled BGP platforms. We mainly focus on the recovery scheme that takes into account BGP routing disruption avoidance at network boundaries, which can be caused by intra-AS failures due to the hot potato routing effect. On top of this scheme, an intelligent IP crank-back operation is also introduced for further enhancement of network protection capability against failures. Our simulations based on both real operational network topologies and synthetically generated ones suggest that, through our proposed optimized backup egress point selection algorithm, as few as two routing planes are able to achieve high degree of path diversity for fast recovery in any single link failure scenario.

Locality-based peer selection paradigms have been proposed recently based on cooperation between peer-to-peer (P2P) service providers, Internet Service Providers (ISPs) and end users in order to achieve efficient resource utilization by P2P traffic. Based on this cooperation between different stakeholders, we introduce a more advanced paradigm with adaptive peer selection that takes into account traffic dynamics in the operational network. Specifically, peers associated with low path utilization as measured by the ISP are selected in order to reduce the probability of network congestion. This approach not only improves real-time P2P service assurance but also optimizes the overall use of network resources. Our simulations based on the GEANT network topology and real traffic traces show that the proposed adaptive peer selection scheme achieves significant improvement in utilizing bandwidth resources as compared to static locality-based approaches.

Efficient Web Services (WS) based network monitoring of managed devices is a difficult task due to the relatively big overhead WS impose. In the past we proposed mechanisms to perform distributed monitoring efficiently, minimizing the relevant overhead. Standardization of WS operations is also important in order to achieve interoperability. The WS Resource Framework (WSRF) tries to standardize the messages exchanged with resources representing the state of a device. Adopting WSRF's concepts, the Management Using Web Services (MUWS) standard aims to support device management in an interoperable manner. In this paper we propose methods to use the mechanisms introduced in our previous work combined with MUWS in order to establish the means to retrieve management information efficiently and at the same time achieve interoperability. We also present our experiences in using custom as well as standardized solutions for monitoring devices that range from small to large resource-capable systems. We describe the motivations for this research and present ideas on techniques that need to be adopted for WS based monitoring based on what we have learned in the process.

Wireless ad hoc networks provide the communications platform for new technologies and applications, such as vehicular ad hoc networks or wireless mesh networks. However, their multihop wireless nature makes them inherently unreliable and vulnerable, since their overall performance depends on the cooperative packet forwarding behavior of each individual node. In this paper we present a role-based approach that uses a distributed management overlay and gathers information about the packet forwarding activities of each node in the network. Using policies to control an adaptive algorithmic method that monitors the individual behavior of each node, we show that it is possible to detect, accuse and punish misbehaving nodes with a high degree of confidence. Our evaluation results demonstrate that after the successful detection of misbehaving nodes, their punishment through network isolation can significantly improve network performance in terms of packet delivery and throughput.

The motivation of the presented thesis emanated from the need for unrestricted wireless communication in a scalable and predictable manner. This need is accentuated by the increasing users' demand for spontaneous communication. The objective is to propose a management framework able to leverage the potential of wireless ad hoc networks as an alternative communication method allowing them to coexist with other networks and to emerge as their flexible extension.

Policy-based management provides the ability to (re-)configure differentiated services networks so that desired Quality of Service (QoS) goals are achieved. This requires implementing network provisioning decisions, performing admission control, and adapting bandwidth allocation to emerging traffic demands. A policy-based approach facilitates flexibility and adaptability as policies can be dynamically changed without modifying the underlying implementation. However, inconsistencies may arise in the policy specification. In this paper we provide a comprehensive set of QoS policies for managing Differentiated Services (DiffServ) networks, and classify the possible conflicts that can arise between them. We demonstrate the use of Event Calculus and formal reasoning for the analysis of both static and dynamic conflicts in a semi-automated fashion. In addition, we present a conflict analysis tool that provides network administrators with a user-friendly environment for determining and resolving potential inconsistencies. The tool has been extensively tested with large numbers of policies over a range of conflict types.

Traffic Engineering (TE) involves network configuration in order to achieve optimal IP network performance. The existing literature considers intra- and inter-AS (Autonomous System) TE independently. However, if these two aspects are considered separately, the overall network performance may not be truly optimized. This is due to the interaction between intra and inter-AS TE, where a good solution of inter-AS TE may not be good for intra-AS TE. To remedy this situation, we propose a joint optimization of intra- and inter-AS TE in order to improve the overall network performance by simultaneously finding the best egress points for inter-AS traffic and the best routing scheme for intra-AS traffic. Three strategies are presented to attack the problem, sequential, nested and integrated optimization. Our evaluation shows that, in comparison to sequential and nested optimization, integrated optimization can significantly improve overall network performance by being able to accommodate approximately 30%-60% more traffic demand.

In this paper we focus on the provision of proportional class-based service differentiation to transmission control protocol (TCP) flows in the context of bandwidth on demand (BoD) split-TCP geostationary (GEO) satellite networks. Our approach involves the joint configuration of TCP-Performance Enhancing Proxy (TCP-PEP) agents at the transport layer and the scheduling algorithm controlling the resource allocation at the Medium Access Control (MAC) layer. We show that the two differentiation mechanisms exhibit complementary behavior in achieving the desired differentiation throughout the traffic load space: the TCP-PEPs control differentiation at low and medium system utilization, whereas the MAC scheduler becomes the dominant differentiation factor under high traffic load. The main challenge for the satellite operator is to appropriately configure those two mechanisms to achieve a specific differentiation target for the different classes of TCP flows. To this end, we propose a fixed-point framework to analytically approximate the achieved differentiated TCP performance. We validate the predictive capacity of our analytical method via simulations and show that our approximations closely match the performance of different classes of TCP flows under various scenarios for the network traffic load and configuration of the MAC scheduler and TCP-PEP agent. Satellite network operators could use our approximations as an analytical tool to tune their networks.

Intra- and inter-AS transient link failures are common in operational IP networks. Robust intra- and inter-AS traffic engineering (TE) schemes have been proposed to optimize network performance against transient link failures. The existing literature has focused solely on either intra- or inter-AS link failure. They have, however, neglected the interactions between robust intra- and inter-AS TE, specifically the impact of intra-AS link failure on inter-AS TE and vice versa. As a result, the overall network performance may not be truly robust to link failures if the interactions are neglected. This paper proposes a joint robust TE approach that takes the interactions into account for achieving good network performance under both normal state and any single intra- or inter-AS link failure. We propose a two-phase heuristic to solve the problem and compare its performance with four alternative approaches that do not consider the interactions. Evaluation results reveal that our joint robust TE approach achieves higher robustness against intra- and inter-AS link failures than all the alternatives.

Web services are an XML-based technology that has been recently viewed as capable of being used for network management. An aspect of WS-based management is monitoring. Monitoring is concerned with the collection of management data reflecting the status of a managed system. WS-based monitoring has to be performed efficiently reducing machine and network resource consumption since in such systems latency, memory and traffic overhead is increased by using XML tags to describe data .This is a big challenge that requires sophisticated mechanisms to retrieve data, such as bulk or selective retrieval to be employed. One technology suggested to address this goal is the XML Path Language. Still XPath as a filtering tool raised a lot of concerns in the NetConf mailing list, about its scalability. Based on these concerns a parser has been developed by the authors to also address data retrieval in network management. This paper is an initial scalability study on these tools to identify potential problems that will need further investigation.

Wireless networks have become a ubiquitous reality and ever more surround our everyday activities. They form and disappear around us spontaneously and have become new means for social interaction. At the same time, their increased complexity and heterogeneity have become barriers to their wider adoption and ease of use. It has become clear that self-management capabilities are vital for truly pervasive network management. To cater for the needs of both service providers and users, we propose a policy-based solution based on the ad hoc networking paradigm. By allowing limited infrastructure support, the notion of ldquohybrid ad hoc networksrdquo emerges as a flexible extension to todaypsilas networks. A distributed policy repository provides the support for policy-based device management and devices can autonomously adapt by examining local conditions and taking corrective actions in real-time. We design a system with self-management capabilities, able to self-configure and self-optimize connectivity parameters. Our aim is to simplify the management of hybrid ad hoc networks, enabling their coexistence and integration with wireless local area networks (WLANs). Implementation and deployment on a wireless testbed have demonstrated significant performance improvement for ad hoc networks in the presence of interference. Our experiments have measured a 33% goodput increase, after switching to a non-interfering channel in real-time.

In recent years we have been introduced to computing environments that integrate wireless and wired components, providing ubiquitous access to information services and applications in a seamless manner. The years to come are expected to be more exciting as we will witness a proliferation in the use of emerging wireless technologies (e.g., sensor networks, vehicular networks, etc.) and enhanced networked applications (e.g., biosensing networks for healthcare, terrestrial ecology observing systems, smart spaces, dynamic communities, etc.) Such increasingly pervasive environments will require new management strategies, which can cope with resource constraints, multi-federated operation, scalability, dependability, context awareness, security, mobility, to mention just a few challenges. The issue to be addressed in this Distinguished Experts Panel is whether we are reinventing the wheel or there are real new challenges ahead. If so, what are they, in which context, and how should we approach them? If not, how can existing management solutions be used/combined/modified/extended in order to address the management needs the emeging ubiquitous environments?

IP Fast ReRoute (FRR) mechanisms have been proposed to achieve fast failover for supporting Quality of Services (QoS) assurance. However, these mechanisms do not consider network performance after affected traffic is rerouted onto repair paths. As a result, QoS deterioration may still happen due to

Modern cities are becoming increasingly networked environments and a plethora of computing equipment interacts with today's urban citizens. We refer to these ubiquitous networked environments as "urban spaces" and attempt to manage these under a unified framework based on policies. Since users actively participate in urban spaces with their owned devices and demand more control and privacy, we introduce a scheme to protect user privacy and respect their preferences. We adopt a multiple manager paradigm to enable more entities to offer their services and cooperatively shape management logic based on their objectives. Detailed policy examples illustrate the concepts and simulation results measure the effect of policies on network performance.

Devices in a mobile ad hoc network (MANET) may misbehave by dropping packets that are forwarded in the network, for example because they are malicious and deliberately intend to disrupt the network or because they are selfish and wish to conserve their own limited resources such as power. In this paper, we present a mechanism that enables the detection of nodes that exhibit packet forwarding misbehavior. We present initial evaluation results that demonstrate the operation of our algorithm and show that it effectively detects nodes that drop a significant fraction of packets.

In this paper we introduce the concepts of Network Planes and Parallel Internets, with the objective of designing and implementing a lightweight solution for viable end-to-end QoS provisioning. The proposed solution can be deployed with very small incremental additions to the existing best-effort Internet. Through Network Plane engineering and interconnection, mainly by means of intra- and inter-domain routing differentiation, end-to-end service differentiation across the Internet can be achieved.

Multicast traffic engineering (TE) has recently attracted significant attention given the emergence of point-to-multipoint multimedia content delivery over the Internet. Existing multicast resource provisioning solutions tend to use explicit-routing based TE with multiprotocol label switching (MPLS) tunnels. In this paper, we shift away from this overlay approach and address native IP multicast traffic engineering based on link state routing protocols. The objective is that, through plain protocol independent multicast-sparse mode (PIM-SM) shortest path routing with optimized multitopology IGP (MT-IGP) link weights, the resulting multicast trees are geared towards minimal consumption of bandwidth resources. We apply genetic algorithms (GA) to the calculation of optimized MT-IGP link weights that specifically cater for engineered PIM-SM routing with statistical bandwidth guarantees in multimedia content delivery. Our evaluation results show that GA-based multicast traffic engineering consumes significantly less bandwidth in comparison to conventional IP approaches while also exhibiting higher service availability

Mobile ad hoc networks (MANETs) are characterized by their heterogeneity and the diverse capabilities of their nodes given that almost any device with a wireless network interface can join such a network. In such an environment it is difficult to dynamically deploy services and protocols without a common understanding among the participating nodes and their capabilities. A deployment/provisioning framework must cope with the high-level of device heterogeneity, degree of mobility, and should also take into account the potentially limited device resources. This paper presents a context-based programmable framework for dynamic service/protocol deployment that allows the nodes of a mobile ad hoc network to download and safely activate required service/protocol software dynamically. Downloading and activation can be triggered through preconditions evaluated according to available contextual information. This strategy leads to the alignment of the nodes' capabilities so that common services and protocols can be deployed even if they are not available at every node. In addition, dynamic context-driven deployment may lead to a degree of network self-optimization. We present the programmable framework and functionality and evaluate its various aspects through testbed experimentation, simulation and analytical modeling. The results demonstrate good performance with respect to the supported functionality.

Inter-AS outbound Traffic Engineering (TE) aims to control the flow of traffic exiting an AS so as to optimize inter-AS TE objectives such as load balancing among multiple downstream ASes. The inter-AS traffic matrix is fundamental input for outbound TE and its accuracy is essential for the target performance to be achieved. However, deriving an accurate traffic matrix is far from trivial. This paper proposes a robust approach for outbound TE to manage traffic demand uncertainty through Scenario-based Robust Optimization. The objective of this robust outbound TE is to minimize the worst-case maximum inter-AS link utilization across a set of inter-AS traffic matrices while minimizing the performance deviation from the optimal solutions. Simulation results reveal that the robust outbound TE is capable of achieving reasonably good performance under all the given traffic matrices while non-robust approaches are not.

Policy-based dynamic resource management may involve interaction between independent decision-making components which can lead to conflicts. For example, conflicts can occur between the policies for allocating resources and those setting quotas for users or classes of service. These policy conflicts cannot be detected by static analysis of the policies at specification-time as the conflicts arise from the current state of the resources within the system and so can only be detected at run-time. In this paper we use policies related to quality of service (QoS) provisioning for configuring differentiated services (DiffServ) networks to illustrate techniques for the dynamic detection and resolution of conflicts. Configuration includes implementing network provisioning decisions, performing admission control, and adapting bandwidth allocation dynamically according to emerging traffic demands. We identify possible conflicts between policies that manage the allocation of resources, and we also investigate conflicts that may arise between these policies and higher-level directives refined at the dynamic resource management level, acting as constraints. The paper shows how event calculus can be used to detect conflicts, focusing on the ones that emerge at run-time, and provides an approach for specifying policies to automate conflict resolution. The latter is demonstrated through our initial implementation of a dynamic conflict analysis tool

Traffic Engineering (TE) is used to optimize IP operational network performance. The existing literature generally considers intra- and inter-AS (Autonomous System) TE independently. However, the overall network performance may not be truly optimized when these aspects are considered separately. This is due to the interaction between intra- and inter-AS TE, where a solution of intra-AS TE may not be a good input to inter-AS TE and vice versa. To remedy this situation, we propose considering intra-AS aspects during inter-AS TE and vice versa. We propose a joint optimization of intra- and inter-AS TE to further improve the overall network performance by simultaneously finding the best egress points for the inter-AS traffic and the best routing scheme for the intra-AS traffic. Three strategies are presented to attack the problem, namely sequential, nested and integrated optimization. Our simulation study shows that, compared to sequential and nested optimization, integrated optimization can significantly improve the overall network performance by accommodating 30%-60% more traffic demands.

Goal-oriented requirements engineering methodologies have been suggested as an alternative to address the policy refinement paradigm. Moreover, practical approaches that capture the administrative and technical requirements to make policy refinement a systematic process are still missing although such integrated solutions are rather convenient to make policy-based management systems really useful. In this paper, we present GOREMOCH, a goal-oriented policy refinement environment grounded in goal-oriented requirements engineering methodologies, linear temporal logic and reactive systems analysis techniques. We describe the rationale of this integrated solution and the necessary mechanisms to achieve policy refinement in a systematic manner

Policy-based management provides the ability to dynamically re-configure DiffServ networks such that desired Quality of Service (QoS) goals are achieved. This includes network provisioning decisions, performing admission control, and adapting bandwidth allocation dynamically. QoS management aims to satisfy the Service Level Agreements (SLAs) contracted by the provider and therefore QoS policies are derived from SLA specifications and the provider's business goals. This policy refinement is usually performed manually with no means of verifying that the policies written are supported by the network devices and actually achieve the desired QoS goals. Tool support is lacking and policy refinement has rarely been addressed in the literature. This paper extends our previous approach to policy refinement and shows how to apply it to the domain of DiffServ QoS management. We make use of goal elaboration and abductive reasoning to derive strategies that will achieve a given high-level goal. By combining these strategies with events and constraints, we show how policies can be refined, and what tool support can be provided for the refinement process using examples from the QoS management domain. The approach presented here can be used in other application domains such as storage area networks or security management.

This paper presents a framework for dynamically organizing mobile nodes (MNs) and electing a dominating-set in highly spontaneous large-scale mobile ad hoe networks (MANETs) with an aim to support location-based routing protocol. The proposed strategy is known as associativity-based clustering, wherein a node is elected as a cluster head (CH) based on nodes having associativity-states that imply periods of spatial and temporal stability. The heuristic that is used in the clustering process ensures a more dynamic, distributed and adaptive operation of our protocol. Furthermore, this heuristic considers mobility of nodes as the main criterion in the cluster head election process, and hence results in stable cluster formation. The heuristic used in our CH election process ensures that the responsibility of acting as cluster heads is evenly distributed among all the nodes, and hence it is fair. Simulation results demonstrate the performance advantages of our strategy.

The rapid emergence of multimedia applications in the Internet has highlighted the need for service differentiation in broadband satellite networks, which aim at being an integral part of the broadband network infrastructure. This paper presents a novel scheduler, called SWTP (satellite waiting time priority), to provide relative service differentiation in a DVB-RCS geostationary (GEO) satellite system where the network is structured to support a finite number of ordered service classes. We advocate the adoption of the proportional service differentiation model in the satellite domain to provide proportional delay differentiation to different traffic classes. The lightweight nature of the model makes it especially suitable for satellite systems as it minimizes computational cost by doing away with mechanisms such as admission control and resource reservation. Simulation results suggest that the SWTP scheduler can effectively and consistently provide proportional delay differentiation in satellite networks.

In differentiated services (DiffServ) domains, where services are provisioned on a per-class basis, admission control is an essential control factor in order to ensure that congestion is avoided and that the quality of service (QoS) requirements of individual flows are met. We consider traffic-engineered and provisioned IP differentiated services domains able to support real-time traffic. We present a new measurement-based admission control (MBAC) scheme that uses measurements of aggregate bandwidth only, without keeping the state of any per-flow information. In our scheme there is no assumption made on the nature of the traffic characteristics of the real-time sources, which can be of any heterogeneous nature. Through simulations we show that the admission control scheme is robust with respect to traffic heterogeneity and measurement errors. We also show that our approach compares favorably against other admission control schemes found in the literature.

Policy-based management provides the ability to dynamically re-configure DiffServ networks such that desired quality of service (QoS) goals are achieved. This includes network provisioning decisions, performing admission control, and adapting bandwidth allocation dynamically. QoS management aims to satisfy the service level agreements (SLAs) contracted by the provider and therefore QoS policies are derived from SLA specifications and the provider's business goals. This policy refinement is usually performed manually with no means of verifying that the policies written are supported by the network devices and actually achieve the desired QoS goals. Tool support is lacking and policy refinement has rarely been addressed in the literature. This paper extends our previous approach to policy refinement and shows how to apply it to the domain of DiffServ QoS management. We make use of goal elaboration and abductive reasoning to derive strategies that achieves a given high-level goal. By combining these strategies with events and constraints, we show how policies can be refined, and what tool support can be provided for the refinement process using examples from the QoS management domain. However, the approach presented here can be used in other application domains such as storage area networks or security management.

Mobile ad hoc networks (MANETs) are characterized by their heterogeneity and the diverse capabilities of the nodes forming the network. Almost any device equipped with a wireless network interface can join an ad hoc network. In such an environment it is difficult to deploy common services without a common understanding among the participating nodes and their capabilities, in terms of processing power, battery life, expected residence time and also in terms of already installed and operational software. This paper presents a middleware-based programmable infrastructure that allows the nodes of a mobile ad hoc network to download and activate required protocol and service software dynamically. This enables the alignment of the nodes' capabilities so that common services and protocols are used among heterogeneous ad hoc network nodes. We first present the middleware functionality and architecture and then evaluate it through both testbed experimentation and simulation. Our evaluation shows that the proposed approach and architecture perform relatively well, with overall convergence time growing linearly with the number of nodes and without any adverse effects because of increasing node density.

Summary form only given, as follows. Next Generation IP-based Networks will offer Quality of Service (QoS) guarantees by deploying technologies such as Differentiated Services (DiffServ) and Multi- Protocol Label Switching (MPLS) for traffic engineering and network-wide resource management. Despite the progress already made, a number of issues still exist regarding edge-to-edge intra-domain and inter-domain QoS provisioning and management. This tutorial will start by providing background on technologies such as DiffServ, MPLS and their potential combination for QoS support. It will subsequently introduce trends in Service Level Agreements (SLAs) and Service Level Specifications (SLSs) for the subscription to QoS-based services It will then move to examine architectures and frameworks for the management and control of QoSenabled networks, including the following aspects: approaches and algorithms for offline traffic engineering and provisioning through explicit MPLS paths or through hopby- hop IP routing; approaches for dynamic resource management to deal with traffic fluctuations outside the predicted envelope; a service management framework supporting a "resource provisioning cycle"; the derivation of expected traffic demand from subscribed SLSs and approaches for SLS invocation admission control; a monitoring architecture for scalable information collection supporting traffic engineering and service management; and realization issues given the current stateof-the-art of management protocols and monitoring support. The tutorial will also include coverage of emerging work towards inter-domain QoS provisioning, including aspects such as: an inter-domain business model; customer and peer provider SLSs; an architecture for the management and control of inter-domain services; inter-domain off-line traffic engineering; and QoS extensions to BGP for dynamic traffic engineering.

The volume of higher priority Internet applications is increasing as the Internet continues to evolve. Customers require quality of service (QoS) guarantees with not only guaranteed bandwidth and delay but also with high availability. Our objective is for each estimated traffic flow to find a primary path with improved availability and minimum failure impact while satisfying bandwidth constraints and also minimizing network resource consumption. We devise a heuristic algorithm with four different cost functions to achieve our objective. Our approach can enhance availability of primary paths, reduce the effect of failure and also reduce the total resource consumption for both primary and backup paths.

This paper proposes a location service to assist location-based routing protocols, realized through a novel Associativity-Based clustering protocol. The main goal of our scheme, which employs hierarchical principles, is to minimize the control traffic associated with location-management. In location-based routing protocols, the control traffic is mainly due to location-updates, queries and responses. Our scheme employs a novel geographically-oriented clustering scheme in order to minimize control traffic without impairing performance. In our location management scheme, nodes are assigned home-zones, and are required to send their location-updates to their respective home-zones through a dominating-set. This strategy, unlike similar location-management approaches, minimizes inevitable superfluous flooding by every node, and prevents location updates and queries from traversing the entire network unnecessarily, hence conserving bandwidth and transmission power. The proposed scheme is evaluated through mathematical analysis and simulations, and the results indicate that our protocol scales well with increasing node-count, node-density and node-speed.

Adaptive clustering is one of the fundamental problems behind autonomic systems and, more generally, an open research issue in the area of networking and distributed systems. The problem of giving structure to large-scale, dynamic systems through clustering and of electing centrally located nodes (cluster heads) is nontrivial. This is in fact an NP-complete problem when striving for optimality. We propose an innovative strategy based on code mobility that dynamically computes near-optimal clusters in linear time. Our approach is autonomic, does not require any user intervention, is self-configuring, self-optimal, and self-healing. We demonstrate these features through an extensive set of simulations, discussing the viability of the algorithm based on state-of-the art technologies, and elaborating on its applicability to distributed monitoring, peer-to-peer systems, application-level multicast, and content adaptation networks.

The primary role of admission control is to decide on the amount of traffic accepted into the network so that users conforming to their established traffic contracts achieve predefined performance objectives, e.g. bounded packet loss probability, end-to-end delay. We consider Diffserv networks able to support real-time traffic and we propose a novel framework for admission control that involves both traffic descriptor and measurement-based techniques and we compare its performance with existing approaches. Our simulation results show that the performance of our approach is rather insensitive to variations of the traffic sources. Even when the provided traffic descriptors are as simple as a single value denoting the required peak rate, the proposed scheme achieves satisfactory performance.

A framework for a proactive network management with the eventual aim to support quality of service (QoS) provisioning in ad hoc networks is proposed in this paper. This process is facilitated through our novel hierarchical clustering approach. This clustering approach is dynamic and distributed, and enables each mobile node (MN) to anticipate the availability of its neighbors through a scalable intelligent mobility prediction algorithm. With the formation of stable clusters, our clustering algorithm enables adaptability, autonomy, economy, scalability and survivability requirements in managing ad hoc networks by adopting policy-based management technique with mobile agent concepts. Initial results demonstrate the stability improvement of our approach.

The primary role of admission control in quality of service enabled networks is to control the amount of traffic injected into the network so that congestion is avoided and certain performance requirements are met. We consider engineered and provisioned IP differentiated services networks able to support realtime traffic and we address the placement of admission control at the traffic aggregation points of the network, and the granularity of the admission control logic. Regarding the first issue, we show that sophisticated admission control schemes that take into account statistical multiplexing gains need only be employed at the first traffic aggregation points. Further downstream, peak rate admission control will suffice. With respect to the second issue, we propose a framework for admission control, which involves a combined approach of traffic descriptor and measurement-based techniques.

Summary form only given. Next generation IP-based networks will offer quality of service (QoS) guarantees by deploying technologies such as differentiated services (DiffServ) and multiprotocol label switching (MPLS) for traffic engineering and network-wide resource management. A number of issues still exist regarding edge-to-edge intra-domain and inter-domain QoS provisioning and management. The tutorial focuses on architectures and frameworks for the management and control of such networks, including the following aspects: emerging service level agreements (SLAs) and service level specifications (SLSs) for the subscription to QoS-based services; management protocols for off-line service negotiation and signaling mechanisms for the dynamic invocation of service instances (e.g., RSVP to the network edge); approaches for the derivation of a traffic matrix based on subscribed SLAs/SLSs and monitoring data; algorithms for off-line traffic engineering and provisioning through MPLS or through plain IP routing with QoS extensions; algorithms for dynamic resource management to deal with traffic fluctuations outside the predicted envelope; a policy-based overall framework for traffic engineering and service management. Finally, ongoing work towards inter-domain QoS provisioning is presented.

Real-time multimedia applications necessitate predictable network resources. Quality of service (QoS) support for such applications in mobile ad hoc networks (MANETs) requires acceptable channel conditions, QoS-aware mechanisms for channel access, identification of proper forwarding (transit) nodes, as well as measures for congestion prevention and management in those nodes. This paper proposes a new QoS-aware medium access control (MAC) protocol that takes the above requirements into consideration. This novel protocol is based on the legacy IEEE 802.11, and thus can be easily integrated into existing systems without much difficulty. Simulation results confirm that our approach results in improved throughput for real-time periodic traffic, while providing deterministic delay performance.

In this paper we present a framework for dynamically organizing mobile nodes (MNs) in large-scale mobile ad hoc networks (MANETs), with the eventual aim to support quality of service (QoS). Our dynamic, distributed clustering approach is based on intelligent mobility prediction that enables each MN to anticipate the availability of its neighbors. We present a scalable way to predict the mobility, and thus availability, of MNs, achieved with the introduction of geographically-oriented virtual clusters. We name the proposed model as the (p, t, d)-clustering model that facilitates the formation of stable clusters. Simulation results demonstrate the performance advantages of our approach.

Given the emergence of IP networks and the Internet as the multi-service network of choice, it is plausible consider its use for transporting demanding multimedia traffic with high bandwidth and low delay and packet loss requirements. Emerging technologies for quality of service such as differentiated services and MPLS can be used for premium quality traffic. We present a traffic engineering and control system that starts from services agreed with customers and provisions the network according to the expected traffic demand so as to meet the requirements of contracted services while optimizing the use of network resources. We devise a non-linear programming formulation of the problem and show through simulations that we can achieve the objectives and meet the requirements of demanding customer traffic.

The deployment of the virtual home environment (VHE) concept in 3G mobile systems in the near future will place many demands on managing a user's personalised service environment. Key to the VHE concept is the performance of such services, resulting in a need to manage quality of service (QoS) demands and allocation on behalf of users. This paper examines the issues involved in managing QoS demands from the various roles and entities in the VHE and proposes a policy-based framework to satisfy their needs.

IP Differentiated Services is widely seen as the framework to provide quality of service (QoS) in the Internet in a scalable fashion. However many issues have still not been fully addressed, such as: the way per-hop behaviours can be combined to provide end-to-end services; the specification of admission control and resource reservation mechanisms; and the role of management plane functionality and its integration with the control and data planes. This paper presents the service management aspects of an integrated control and management architecture for supporting end-to-end QoS-based IP services in next generation networks. It introduces a two-phased approach for service negotiation, namely, service subscription followed by service invocation, and describes the interworking between service and resource management based on the concept of a resource provisioning cycle.

Bi-directional shared tree is an efficient routing scheme for many-to-many multicast applications (e.g. multiparty videoconferencing, interactive distance lecturing and Internet games etc). Given the open-group IP multicast service model, it is important to perform sender access control so as to prevent group members from receiving irrelevant data, and also protect the multicast tree from various Denial-of-Service (DoS) attacks. In comparison to source based and unidirectional shared trees where the data source can be authorized or authenticated at the single root or rendezvous point, in bi-directional routing this is a much more difficult problem since hosts can send data to all group members directly from any point in the tree. In this paper we propose a dynamic sender access control mechanism for bi-directional multicast trees so that irrelevant data is policed and discarded as it reaches any on-tree router. We show through simulation that the overhead of our mechanism is relatively small in terms of required state information in routers so that the proposed approach scales well for large groups.

Networks offering services of high availability and quality need to be carefully monitored. Their increasing size and complexity stresses the ability of currently used static centralized systems. Decentralized approaches are possible and a key issue is the placement of area monitoring stations for optimal operation. Previous research has resulted in computationally expensive algorithms that require a global centralized network view. In this paper we propose a much simpler distributed algorithm and show that it performs as well as existing near-optimal but expensive, centralized algorithms. In addition, we propose that area monitoring stations are mobile agents, cloning and optimally placing themselves by executing the proposed algorithm. As network conditions change, e.g. through faults or persisting congestion, agents can adapt and migrate to new locations. We quantify the benefits of our approach against both the centralized and centrally-computed static distributed approaches.

As the Internet evolves, a key consideration is support for services with guaranteed quality of service (QoS). The proposed differentiated services (DiffServ) framework, which supports aggregate traffic classes, is seen as the key technology to achieve this. DiffServ currently concentrates on control/data plane mechanisms to support QoS but also recognises the need for management plane aspects through the bandwidth broker (BB). In this paper we propose a model and architectural framework for supporting end-to-end QoS in the Internet through a combination of both management and control/data plane aspects. Within the network we consider control mechanisms for traffic engineering (TE) based both on explicitly routed paths and on pure node-by-node layer 3 routing. Management aspects include customer interfacing for service level specification (SLS) negotiation, network dimensioning, traffic forecasting and dynamic resource and routing management. All these are policy-driven in order to allow for the specification of high-level management directives. Many of the functional blocks of our architectural model are also features of BBs, the main difference being that a BB is seen as driven purely by customer requests whereas, in our approach, TE functions are continually aiming at optimising the network configuration and its performance. As such, we substantiate the notion of the BB and propose an integrated management and control architecture that will allow providers to offer both qualitative and quantitative QoS-based services while optimising the use of underlying network resources.

This contribution presents a prototype of network management framework based on distributed plug-in component technology. The main innovative aspect is the exhibited capacity to facilitate network management applications to be reconfigured at runtime by changing the communication channels used by the constituent components to communicate. This adds great flexibility because the system functionality is not "closed" at the system design time. The ensemble constitutes a development framework for component-based management applications. A scenario is presented to demonstrate the system in action.

It is broadly accepted that the telecommunications industry is undergoing a fundamental restructuring. This is driven by new customer demands and by changes in the regulatory environment, and is both enabled and encouraged by rapid technological developments. Additionally, the demand for new sophisticated telecommunications services with multimedia characteristics is increasing. These services require more flexible access, management, and charging mechanisms. Thus, it is necessary to assist, in a systematic manner, telecommunications service designers in the development of new services. In this paper, after an examination of important service engineering matters, a service creation methodology is proposed and presented focusing on its essential characteristics. A possible enhancement of this methodology through the use of design patterns and frameworks is then considered.

A research issue under investigation in the context of differentiated services (DiffServ) is the fair distribution of bandwidth between aggregates sharing the same assured forwarding (AF) class. Multiplexing both responsive and unresponsive flows, e.g. TCP and UDP respectively, leads to unfair sharing of the available bandwidth in over-provisioned networks. To date, much effort has concentrated on experiments using different methods for mapping TCP and UDP flows of the same AF class to the three possible drop precedences of the AF specification. Although this approach may protect responsive from unresponsive flows, it has not been shown to provide adequate fairness. We present a traffic conditioner able to provide fairness between responsive and unresponsive flows originating from the same customer network, using a fair two-rate three-color marker. Its capability for fairness is based on the use of the FRED fair active buffer algorithm to control the token allocation of the token buckets residing in the traffic conditioner. We also show that by employing fair multiple RED (FMRED) at the DiffServ domain ingress node, the overall fairness of the customer network aggregates is improved when compared to the case where the vanilla MRED algorithm is used.

In the emerging deregulated multi-provider telecommunications market place, telecommunications service engineering, enhanced with the architectural framework of the Telecommunications Information Networking Architecture Consortium (TINA-C), promises to pave the way towards an open integrated broadband service infrastructure. In order to be able to populate this infrastructure with a variety of new (sophisticated) telecommunications services, it is necessary to assist and constrain service designers during the complex process of service creation. Therefore, in this paper, after considering briefly a number of service modelling issues, a TINA-C conformant service creation methodology, based on the exploitation of the flexible Unified Modelling Language (UML) notation, is proposed. This methodology is then presented focusing on the role and purpose of essential artifacts, examining their dependencies and illustrating the significance of UML.

Mobile agent frameworks have attracted a lot of attention in recent years, seen as counterparts of static distributed object frameworks but allowing also for object or agent mobility. A lot of research is currently being carried out trying to assess their applicability to network management and control environments. In this paper, we present our experiences of using a mobile agent framework to design and realize a performance management system which exhibits "constrained mobility", constrained in the sense that performance monitoring agents are sent to execute within network elements and stay there until their task is accomplished. We present the architecture, design and implementation of such a system, compare and contrast it to static object approaches and present a detailed performance comparison to a similar Java-RMI based implementation, trying to assess the overhead of mobile agent solutions.

This paper addresses a number of issues related to the evolution of the TMN framework in terms of the associated interface technology. A review of the management model is followed by an analysis of the challenges raised by emerging distributed object architectures which may result in highly distributed management systems; from these, fundamental requirements for CORBA-based TMN agent architectures are derived. The paper describes two approaches for realising CORBA-based management agents that attempt to fulfil these requirements. Both approaches have been validated through implementation while operational experiences with the two approaches are presented.

The Telecommunications Management Network (TMN) has been developed as the framework to support administrations in managing telecommunications networks. It suggests the use of OSI Systems Management (OSI-SM) as the technology for management information exchanges. Distributed object technologies, such as the Common Object Request Broker architecture (CORBA), address the use of software application program interfaces (APIs) in addition to interoperable protocols. Their use in TMN has been the subject of intensive research in previous years, with most approaches focusing on interoperability aspects with OSI-SM. We examine the issues behind using distributed object technologies in TMN via a native fashion, with network elements supporting distributed objects directly, e.g., a "CORBA to the switch" approach. The proposed solution tries to maintain the full OSI-SM expressive power in a way that other solutions have not attempted before. Performance and scalability issues are considered, while the approach has been validated through implementation.

Over the last few years, OMG CORBA has been emerging as the ubiquitous technology for building distributed systems. Since the TMN is a distributed system, a lot of research has addressed the issue of using CORBA as its base technology. Most solutions have concentrated mainly on interoperability aspects between OSI-SM and CORBA, assuming that OSI-SM will be used at the TMN element and element management level. In this paper we examine the issues behind a native CORBA-based TMN, trying to achieve a solution that maintains the full OSI-SM expressive power while it is at the same time scalable and performant. While elements of other solutions are used, e.g., the JIDM GDMO to IDL mappings, a number of aspects in this proposal are novel. In particular, CMIS-like access aspects through scoping and filtering are kept separate from managed objects. In addition, managed objects are not required to have distinct IDL interfaces but agents may become computational entities with CMIS-like IDL interfaces. The approach has been partly validated through implementation while relevant CORBA-based applications were used in field trials.

Distributed Network Management is gaining importance due to the explosive growth of the size of computer networks. New management paradigms are being proposed as an alternative to the centralised one, and new technologies and programming languages are making them feasible. The use of Mobile Agents (MAs) to distribute and delegate management tasks is a particularly promising approach to dealing with the limitations of current centralised management systems which appear to be lacking flexibility and scalability. This paper is focused on the impact that mobile code paradigms can have on distributed network and system monitoring. A dynamic, hierarchical management model based on a delegation paradigm is adopted and an MA-architecture for monitoring operations is proposed. Finally, possible uses of the proposed model and architecture for pursuing seamless and timely monitoring are discussed.