Microservice applications, composed of independent containerized components, are well-suited for hybrid cloud–edge deployments. In such environments, placing microservices at the edge can reduce latency but incurs significantly higher resource costs compared to the cloud. This paper addresses the problem of selectively replicating microservices at the edge to ensure that the average user-perceived delay remains below a configurable threshold, while minimizing total deployment cost under a pay-per-use model for CPU, memory, and network traffic. We propose a greedy placement strategy based on a novel analytical model of delay and cost, tailored to synchronous request/response applications in cloud–edge topologies with elastic resource availability. The algorithm leverages telemetry and load balancing capabilities provided by service mesh frameworks to guide edge replication decisions. The proposed approach is implemented in an open-source Kubernetes controller, the Geographical Microservice Autoplacer (GMA), which integrates seamlessly with Istio and Horizontal Pod Autoscalers. GMA automates telemetry collection, cost-aware decision making, and geographically distributed placement. Its effectiveness is demonstrated through simulation and real testbed deployment.

With the rapid expansion of IoT, there is a growing demand for efficient data processing and network load optimization. Service Function Chaining (SFC) has emerged as a key technology for distributed processing, particularly in edge computing environments. While SFC is traditionally implemented over IP networks, recent research has explored Named Data Networking (NDN) as a more flexible alternative, leveraging its content caching and name-based forwarding. However, NDN’s inherent request aggregation and multicast mechanisms introduce unique challenges in applying conventional distributed tracing techniques, which are crucial for SFC applications to understand potential root causes of problems.This paper proposes a distributed tracing method for NDN-based SFC (NDN SFC) that enables packet flow visualization and network latency analysis. Our method introduces logging agents on NDN routers to capture request flows and inter-node delays, which are then formatted using OpenTelemetry for seamless integration with visualization tools such as Grafana®and Jaeger.Our tracing method helps to optimize service chains, to enhance network performance evaluation, and to streamline debugging, making NDN SFC deployment more practical. By offering a more efficient alternative to traditional IP-based SFC, our method supports the practical adoption of NDN SFC in IoT and edge computing environments.

Federated testbeds enable collaborative research by providing access to diverse resources, including computing power, storage, and specialized hardware like GPUs, programmable switches and smart Network Interface Cards (NICs). Efficiently sharing these resources across federated institutions is challenging, particularly when resources are scarce and costly. GPUs are crucial for AI and machine learning research, but their high demand and expense make efficient management essential. Similarly, advanced experimentation on programmable data plane requires very expensive programmable switches (e.g., based on P4) and smart NICs. This paper introduces SHARY (SHaring Any Resource made easY), a dynamic reservation system that simplifies resource booking and management in federated environments. We show that SHARY can be adopted for heterogenous resources, thanks to an adaptation layer tailored for the specific resource considered. Indeed, it can be integrated with FIGO (Federated Infrastructure for GPU Orchestration), which enhances GPU availability through a demand-driven sharing model. By enabling real-time resource sharing and a flexible booking system, FIGO improves access to GPUs, reduces costs, and accelerates research progress. SHARY can be also integrated with SUP4RNET platform to reserve the access of P4 switches.

Service meshes are becoming pivotal software frameworks for managing communication among microservices in distributed applications. Each microservice in a service mesh is paired with an L7 sidecar proxy, which intercepts incoming and outgoing requests to provide enhanced observability, traffic management, and security. These sidecar proxies use application-level load balancing policies to route outgoing requests to available replicas of destination microservices. A widely adopted policy is the Least Outstanding Request (LOR), which directs requests to the replica with the fewest outstanding requests. While LOR effectively reduces latency in applications with a small number of replicas, our comprehensive investigation– combining analytical, simulation, and experimental methods– uncovers a novel and critical issue for large-scale microservice applications: the performance of LOR significantly degrades as the number of microservice replicas increases, eventually converging to the performance of a random load balancing policy. To recover LOR performance at scale, we propose an opensource solution named Proxy-Service, tailored for microservice applications where load balancing incurs significantly lower resource demands than microservice execution. The core idea is to consolidate load balancing decisions per microservice into one or a few reverse proxies, transparently injected into the application.

Container technology plays an important role in the virtualization landscape today. A container uses its own file system consisting of a stack of layers, which are stored on the execution server's disk. Containers running on the same server share the layers they have in common, and this sharing results in valuable savings in server storage space. Many containers can run on a single server, but when their resource demands grow enough, they are distributed across a cluster of nodes/servers by orchestration systems, such as Kubernetes. In this work, we found that for the same amount of containers to run, the storage required is higher for clusters consisting of a larger number of nodes. The severity of this storage overhead depends on the scheduling policy used to select the nodes that run the containers. By comparing different storage-saving scheduling policies that differ from each other in the depth of storage knowledge they leverage to make decisions, our analysis reveals that only deep, layer-level knowledge can effectively counter the growth in storage demand as the cluster size increases. Policies with coarser-grained knowledge achieve limited benefit because they achieve performance that is nearly equal to that of a random, zero-knowledge policy.

$\mu$Bench is an open-source tool for benchmarking cloud/edge computing platforms that run microservice applications. The tool creates dummy microservice applications that can be customized and executed on a Kubernetes cluster.$\mu$Bench allows users to control fundamental properties of the microservice applications it creates, such as service mesh topology, microservices’ behaviors using a portfolio of stress functions (e.g., for CPU, memory, I/O, network) or implementing new ones, microservice-to-microservice API (HTTP or gRPC), etc. Application performance can be evaluated by stochastic or trace-driven workloads. μBench is aimed at researchers and cloud platform developers who lack real microservice applications to benchmark their findings (e.g., new resource control mechanisms, artificial intelligence-driven orchestration, etc.) or wish to thoroughly evaluate their proposals versus a broad set of heterogeneous applications that μBench can create. In addition to the description of μBench, in this article, we show one possible use of it. We compared advantages and disadvantages of microservice architectures versus monolithic ones, and analyzed the performance impact of key architectural choices, such as service mesh topology and the use of replication. For this analysis, we generated several microservice applications with different properties, and two of them are derived from a real cloud dataset.

Message Queuing Telemetry Transport (MQTT) is a widespread protocol for topic-based publish-subscribe architectures supporting IoT and social networks applications. MQTT brokers are logical entities that couple publishers and subscribers and play a critical role in such architectures. MQTT brokers can be implemented either as standalone servers or in a cluster configuration. Clusters of brokers increase reliability, availability and overall performance, since operations can be highly parallelized among the brokers that form the cluster. The load-balancing strategy in a cluster usually consists in connecting an incoming client to a randomly selected broker. This random-attach strategy, it is very simple, but generates a significant amount of inter-broker traffic, as we demonstrate through theoretical and experimental evaluations. Inter-broker traffic is an overhead for the system and it increases the CPU load of the brokers, compromising the scaling behavior of the whole cluster. Indeed, we found that a linear increase of the number of brokers forming a cluster does not necessarily provide an equivalent linear gain in performance, and such a scaling penalty can be surprisingly significant, in the order of 40%. To solve this issue and improve performance, we propose a novel load-balancing strategy that envisages the use of multiple MQTT sessions per client to reduce inter-broker traffic and that can be implemented by means of a greedy algorithm. We show feasibility and effectiveness of our strategy for IoT and social-network applications by means of simulations and real measurements. The resulting scaling penalty is reduced to 10%.

The expected dramatic growth of connected things raises the issue of how to efficiently organize them, in order to monitor and manage functions and interactions. Information centric networking (ICN) is a communication paradigm that provides content-oriented functionality in the network and at the network level, including content routing, caching, multicast, mobility, data-centric security, and a flexible namespace. Thus, it is a viable solution for supporting Internet of Things (IoT) services without requiring any centralized entity. In this paper, we introduce the lightweight named object solution: a convenient way to represent physical IoT objects in a derived name space, exploiting ICN. We show that this abstraction can: 1) increase the programming simplicity; 2) offer extended functionality, such as augmentation and upgrading, to cope with the “software erosion,” and 3) implement a common interaction logic involving mutual function invocation. We present some proof-of-concept implementations of the proposed abstraction dealing with challenging IoT test cases; we also carry out a performance evaluation in a simulated network scenario.

This paper explores methodologies, advantages and challenges related to the use of the Information Centric Network technology for developing NoSQL distributed databases, which are expected to play a central role in the forthcoming IoT and BigData era. ICN services make possible to simplify the development of the database software, improve performance, and provide data-level access control. We use our findings to design a NoSQL spatio-temporal database, named OpenGeoBase, and evaluate its performance by using a real data set relevant to Intelligent Transport System applications.

This paper describes a demo of OpenGeoBase, a NoSQL spatio-temporal distributed database that exploits Information Centric Network technology. We show its basic operations and two applications based on it. The first one is an Intelligent Transport System application making possible to discover public transport information (GTFS files) all over the world. The second application concerns a citizen reporting application though which users can post and search for geo-tagged photos.

MPEG DASH is a widely used standard for adaptive video streaming over HTTP. The conceptual architecture for DASH includes a web server and clients, which download media segments from the server. Clients select the resolution of video segments by using an Adaptive Bit-Rate (ABR) strategy; in particular, a throughput-based ABR is used in the case of live video applications. However, recent papers show that these strategies may suffer from the presence of proxies/caches in the network, which are instrumental in streaming video on a large scale. To face this issue, we propose to extend the MPEG DASH architecture with a Tracker functionality, enabling client-to-client sharing of control information. This extension paves the way to a novel family of Tracker-assisted strategies that allow a greater design flexibility, while solving the specific issue caused by proxies/caches; in addition, its utility goes beyond the problem at hand, as it can be used by other applications as well, e.g. for peer-to-peer streaming.

This paper presents an Android application exploiting a collaborative multi-RAT approach (cellular and Wi-Fi Radio Access Technologies) for adaptively streaming video content. The application has been developed and tested on real Android devices of different vendors. Each device coordinates with the others to download portions of a video stream through its own preferred RAT, and shares the results with the neighboring devices through a proximity, high bit rate network based on Wi-Fi Direct. As a result, the aggregate bandwidth available to the group of collaborating devices allows a faster download and a higher quality of video playback streaming, with respect to what is achievable by a single device. The application is designed to exploit common Android devices along with the key functionalities of an Information Centric Network: routing-by-name, in-network caching and multicasting.

Information Centric Networking (ICN), a novel network paradigm, places the focus on the content instead of the end-hosts. ICN addresses content by names instead of locations and can ease content retrieval and improve network efficiency. Ongoing work attempts to extend the use of ICN to scenarios such as real time communication, group communication, push services, and addresses the issue of migration from the current network and coexistence of different network paradigms. In this work, we argue that by extending the current design of ICN from a “host-to-name” to a “name-to-name” architecture, the utility and efficiency of ICN could be further increased. We propose Internames, an architectural framework in which names are used to identify all entities involved in communication: content, users, devices, logical points, and services. Internames is envisioned to be an overarching name-to-name communication primitive that is fully compatible with ICN principles, accommodates the coexistence (or gradual migration) of different network realms (e.g., IP, ICN, VANET) and is suitable for application scenarios where ICN is somehow limited by its reliance on a “host-to-name” approach. In this paper, we provide early insights into the Internames architecture by leveraging on the work done by the research community and identify components and challenges that require more detailed investigation.

Information Centric Networking (ICN) is paradigm in which the network layer provides users with content addressed “by name”. In-network caching is one of the key functionality to be provided by ICN nodes. To avoid network nodes caching fake contents, it is necessary to verify the validity of data items. A content is deemed to be valid if it verifies three properties: i) integrity: it has not be modified; ii) provenance: it comes from the intended source; iii) relevance: it is indeed the content requested from the user (by using the name of that content). In this paper, we discuss the interplay among three pivotal ICN aspects: caching, validity and naming. Specifically, we will investigate different naming and digital signature schemes, evaluating their speed, overhead and their impact on caching performance. Perhaps counter-intuitively, we find that the relatively slow verification time of today's signatures, which bottlenecks the rate of storing new data items in the network caches, does not come as a critical shortcoming, but may actually even improve the cache hit probability when the LRU caching policy is employed.

Information Centric Networking (ICN) is a new paradigm in which the network layer provides users with content exposed as names, instead of providing communication channels between hosts. We present a P2P application for the live streaming of video contents encoded at multiple bit-rates. The application enables a limited set of neighboring cellular devices to increase the quality of video playback, by cooperatively using their cellular (e.g. 3G) and proximity (e.g. Wi-Fi Direct) wireless connections. The application exploits key functionalities of ICN: routing by name, in network caching and multicast delivery. We developed a prototype of the application and assessed its performance in a test-bed based on Linux devices with 3G connections, the CCNx tool, the VLC player and the MPEG DASH streaming format. Our main contribution is to show how ICN can provide support to emerging video streaming applications, and ease their creation.

In this paper we propose to integrate Software Defined Networking (SDN) principles in Wireless Mesh Networks (WMN) formed by OpenFlow switches. The use of a centralized network controller and the ability to setup arbitrary paths for data flows make SDN a handy tool to deploy fine-grained traffic engineering algorithms in WMNs. However, centralized control may be harmful in multi-hop radio networks formed by commodity devices (e.g. Wireless Community Networks), in which node isolation and network fragmentation are not rare events. To exploit the pros and mitigate the cons, our framework uses the traditional OpenFlow centralized controller to engineer the routing of data traffic, while it uses a distributed controller based on OLSR to route: i) OpenFlow control traffic, ii) data traffic, in case of central controller failure. We implemented and tested our Wireless Mesh Software Defined Network (wmSDN) showing its applicability to a traffic engineering use-case, in which the controller logic balances outgoing traffic among the Internet gateways of the mesh. Albeit simple, this use case allows showing a possible usage of SDN that improves user performance with respect to the case of a traditional mesh with IP forwarding and OLSR routing. The wmSDN software toolkit is formed by Open vSwitch, POX controller, OLSR daemon and our own Bash and Python scripts. The tests have been carried out in an emulation environment based on Linux Containers, NS3 and CORE tools.

Information Centric Networking (ICN) is a new paradigm in which the network layer provides users with content, instead of providing communication channels between hosts, and is aware of the name (or identifiers) of the contents. In this paper, we first describe what, we believe, are the main advantages and components of an ICN infrastructure; then we present an overall architecture for ICN, and then we focus on the main contribution of the paper, which is a route caching technique, designed to improve the scalability of the routing by name functionality.

The Information-Centric Networking (ICN) paradigm is expected to be one of the major innovation of the Future Internet An ICN can be characterized by some key components like: (i) the content-centric request/reply paradigm for data distribution, (ii) route-by-name operations, and (iii) in-network caching. In this paper we focus on a framework for ICN called CONET (COntent NETwork) and in particular on a solution devised under this framework called coCONET. coCONET characteristics make it suitable for deployment in accordance to the Software Defined Networks (SDN) philosophy. In this paper, we will describe how coCONET can be implemented over an OpenFlow (the most popular SDN instantiation, to date) network and how OpenFlow should be modified to better suit the operations of coCONET and, more in general, of ICN solutions.

In this paper we present a cooperative video streaming application running on top of an “Information Centric Network” (ICN). The application could be used on mobile devices to offload the cellular radio interface. We demonstrate our application in a test-bed exploiting the CCNx software implementation of an ICN, the VideoLan tool and the Apple HTTP Live Streaming format.

Wireless community networks are mesh networks built by volunteers which own, configure, and manage their wireless node. Such networks are prone to either unintentional (e.g. misconfiguration) or intentional node misbehavior. This paper proposes a fully distributed trust-based routing framework, tightly integrated with OLSR, which is the most exploited routing protocol in real world wireless community networks. The framework, designed to be modular for easy upgrade, relies on active probes, hidden in the normal data traffic through adaptation of steganography techniques. The combination of path-wide measurements into a distributed trust-framework, preliminary based upon the well known EigenTrust mechanism, permit to infer whether, and which, packet-droppers (i.e. nodes misbehaving at the data plane) affect the network forwarding operation. The resulting per-node trust values are then transformed into suitable "weights" provides as input to the OLSR protocol for mitigation through re-routing. A simulation-based performance evaluation shows that the proposed framework appears already effective in detecting and circumventing packet-droppers, despite the relative simplicity of the preliminarily considered algorithms.

The aim of this extended abstract is to present Campus++, a location-based publish-subscribe system for intermittently connected delay tolerant networks, exploiting IEEE 802.15.4 devices, and taking into due account the severe constraints deriving from their physical characteristics. We describe our proposed architectural model and how we implemented our solution in a real test-bed. We point out that our system can be easily adapted to operate in a fully distributed, infrastructure-less way, allowing free communications e.g. in disaster areas or in areas in which ”usual” communications means are either non existent or intentionally made unavailable.

In this paper we present a Robust data Replication Algorithm (RRA) for MANETs. RRA ensures persistent data availability by duplicating data over replica-nodes, while minimizing the consumption of radio resources. RRA is the first algorithm thoroughly designed to operate in environments with node failures and radio obstacles (e.g., buildings, walls). Our challenge is to consider such impairments as "accidental"; i.e., their occurrence neither can be run-time predicted, nor can be a-priori quantified in terms of probability. As instance, this is the case of nodes wandering in an unknown territory. To cope efficiently with the novel challenge, we suggest a practical assumption: during a refresh period, only a single accidental impairment may occur. Following this assumption, we succeed in formalizing (and solving) the resource minimization problem as the finding of a minimum-cost-set-cover. We assess RRA performance through NS2 simulations. Simulation code is released as open-source.

Thanks to its in-network drop-based adaptation capabilities, H.264 Scalable Video Coding is perceived as an effective approach for delivering video over networks characterized by sudden large bandwidth fluctuations, such as Wireless LANs. Performance may be boosted by the adoption of application-aware/cross-layer schedulers devised to intelligently drop video data units (NALUs), so that i) decoding dependencies are preserved, and ii) the quality perceived by the end users is maximized. In this paper, we provide a theoretical formulation of a QoE utility-optimal cross-layer scheduling problem for H.264 SVC downlink delivery over WLANs. We show that, because of the unique characteristics of the WLAN MAC operation, this problem significantly differs from related approaches proposed for scheduled wireless technologies, especially when the WLAN carries background traffic in the uplink direction. From these theoretical insights, we derive, design, implement and experimentally assess a simple practical scheduling algorithm, whose performance is very close to the optimal solution.

The Data Distribution Service (DDS) middleware is enjoying a rapid adoption in high-performance, mission-critical networks. At the same time, the H.264 Scalable Video Coding (SVC) has been recently standardized and it is deemed to be an effective solution for video streaming over a channel with time-varying bandwidth, like the wireless one. In these conditions, it is critical to adapt the video bit-rate to the actual wireless capacity, and bit-rate adaptation is extremely simple for a H.264 SVC video. In this paper we devise, evaluate and demonstrate a technique for streaming H.264 SVC video over a DDS middleware. The contribution is threefold: i) we design a structure of the DDS data-unit able to carry H.264 SVC video-units; ii) we devise a receiver-driven rate-control mechanism based on our DDS data-unit and exploiting specific DDS functionality; iii) we implement and show the effectiveness of our mechanism in an 802.11 wireless scenario, comparing our proposal with other solutions.

Abstract The WiMAX system carries a wide range of services in urban and rural environments supporting quality of service. A key element of the QoS framework is the scheduling algorithm adopted by the Base Station (BS). In this paper, we analyze the saturation throughput perceived by Mobile Stations in the cases of two BS scheduling algorithms: Deficit Round Robin (DRR) and time‐based DRR. We demonstrate that the WiFi issue of ‘Performance Anomaly’ also occurs in WiMAX networks: when the BS uses scheduling approaches aimed at achieving throughput‐fairness, like DRR. Performance Anomaly means that when some Mobile Stations (MSs) use a very low bit rate, the throughput of MSs with a high bit rate is dramatically degraded. We propose time‐based DRR as a viable solution to remove the Performance Anomaly. Time‐based DRR is a simple modification of the DRR algorithm that achieves time‐fairness. Its implementation is feasible in WiMAX. The analysis is carried out by means of analytical models supported by NS2 simulations. Two scenarios are considered: the first is suitably set up to highlight and understand the phenomenon of Performance Anomaly; the second examines the impact of Performance Anomaly on a system level focusing on a rural environment. Copyright © 2008 John Wiley & Sons, Ltd.

This paper describes the H.264 scalable video coding streaming evaluation framework (SVEF). This is the first open-source framework for experimental assessment of H.264 scalable video coding (SVC) delivery over real networks. Effectively adapting of the transport of an H.264 SVC stream to time-varying, bandwidth constrained, and loss prone networks is an important research area. However, very little experimental work has been performed due to the unavailability of real-time H.264 SVC players, the limitations of existing decoding software libraries when challenged with network-imparied received SVC streams (e.g., affected by random loss of Network Abstraction Layer Units - NALUs), and the lack of solutions for SVC streaming support. SVEF overcomes these issues by developing missing components and by integrating them in a hybrid online/offline experimental framework. We believe SVEF will be of significant help to the research community interested in experimentally benchmarking their own proposed SVC adaptation approaches and delivery mechanisms. As a proof-of-concept of SVEF, we provide the experimental performance evaluation of an SVC cross-layer in-network scheduler in a wireless LAN hot spot scenario.

In this paper we evaluate analytically the average occupancy of the transmission buffer of a 802.11 station (STA). The station belongs to a Wi-Fi Hot-Spot and exchanges data with a fixed host. The data exchange is regulated by the Transmission Control Protocol (TCP). The research interest is motivated by the fact that several papers assume that in these conditions the STA buffer is nearly empty. On the contrary, we prove that this assumption may be wrong and discuss the consequences of this fact. We test the proposed model by means of ns2 simulation, ascertain its accuracy, and highlight its limits.

Abstract This paper presents a novel Mobile Ad‐hoc NETworks (MANET) multicast protocol, named Overlay Borůvka‐based Ad‐hoc Multicast Protocol (OBAMP), and evaluates its performance. OBAMP is an overlay protocol: it runs only in the end‐systems belonging to the multicast group. OBAMP has three distinctive features, which give to the protocol a good performance in terms of distribution efficiency: (i) its distribution tree closely resembles the minimum spanning tree; (ii) it exploits broadcast communications; (iii) its design limits not only overlay signaling but also network‐layer signaling. In addition, OBAMP can cope with node failures in a very short time. As a consequence, OBAMP has a low latency and a high delivery ratio, even when the group size increases. To prove these statements, we analyze the performance of OBAMP with ns‐2 and compare it with three state‐of‐the‐art protocols, namely ODMRP (a network‐layer protocol), ALMA, and AMRoute (two overlay protocols). The overlay protocols are assumed to use AODV as underlying routing protocol. Also, we stress that we have implemented OBAMP, in Java, and we have tested it on the field, to prove its feasibility; to allow fellow researchers to reproduce and test our work we published all simulation and implementation codes. Copyright © 2007 John Wiley & Sons, Ltd.

This work presents a novel MANET multicast protocol, named overlay Boruvka-based ad-hoc multicast protocol (OBAMP), and evaluates its performance. OBAMP is an overlay protocol: it runs only in the end-systems belonging to the multicast group. User data are distributed over a shared distribution tree formed by a set of non-cyclic UDP tunnels. OBAMP derives the distribution tree by approximating the Boruvka algorithm; the Boruvka algorithm is a classical tool (1926) to find the minimum spanning tree; thus, the distribution tree of OBAMP is an approximation of the minimum spanning tree of the connectivity topology at hand. OBAMP shows three distinctive advantages: i) its distribution tree closely resembles the minimum spanning tree; ii) it exploits broadcast communications (with favourable consequences on its efficiency); iii) its design takes into account not only overlay signalling but also network-layer signalling; thus, the protocol succeeds in limiting the overall signalling load, network+overlay. As a consequence, OBAMP has a low-latency and a high delivery ratio, even when the group size increases. To prove this statement, we analyze the performance of OBAMP with ns-2 and compare it with two state-of-the-art protocols, namely ODMRP (a network-layer protocol) and ALMA (an overlay protocol). Both OBAMP and ALMA are assumed to use AODV as underlying routing protocol. Also, we stress that we have implemented OBAMP, in Java, and we have tested it on the field, to prove its feasibility. To allow fellow researchers to reproduce and test our work we published all simulation and implementation codes, in www.radiolabs.it/obamp.

In this paper, we study the problem of maintaining fairness for TCP connections in wireless local area networks (WLANs), based upon the IEEE 802.11 standard and operating in DCF mode. Although this mode of operation ensures fair access to the medium at the MAC level, it does not provide fairness among TCP connections. TCP unfairness may result in significant degradation of performance, leading to users perceiving unsatisfactory quality of service. We propose and analyze a solution capable of enabling TCP fairness with minimal additional complexity. The proposed solution is based on utilizing an IP rate-limiter with an adaptive rate control mechanism and does not require modifying existing standards at the MAC or network layers. The solution is fully compatible with existing devices and can be integrated either within the access point or within and external device (e.g., the network gateway). The performance analysis is performed in a real test-bed and proves the feasibility and effectiveness of our mechanism. To allow fellow researchers to reproduce our work we published on the WEB all the implementation code.

In this paper, we study the problem of maintaining fairness for TCP connections in wireless local area networks (WLANs) based upon the IEEE 802.11 standard. Current implementations of 802.11 use the so-called distributed coordination function (DCF), which provides similar medium access priority to all stations. Although this mode of operation ensures fair access to the medium at the MAC level, it does not provide any provisions for ensuring fairness among the TCP connections. TCP unfairness may result in significant degradation of performance leading to users perceiving unsatisfactory quality of service. We propose and analyze two solutions that are capable of enabling TCP fairness with minimal additional complexity. The proposed solutions are based on utilizing a rate-control mechanism in two modes: static or adaptive. They do not require modifying existing standards at the MAC or network layers. Hence, they are fully compatible with existing devices. Our performance analysis results prove the efficaciousness of our proposed solutions in achieving TCP fairness compared to existing approaches. We have, also, implemented the proposed solutions in an ad-hoc experimental test-bed, and performed measurements to demonstrate the validity of our approach and results

This paper investigates the effectiveness of the application level multicasting, named overlay multicasting, with respect to the network layer one in mobile ad hoc networks (MANET). With respect to the network layer multicasting in overlay multicasting, only the mobile nodes participating in the multicast group have exploited the multicast routing at the application level while the other nodes of the MANET simply perform unicast IP routing. This constraint in the possibility of using multicast routing in all the nodes that leads to a loss of efficiency in the bandwidth usage are discussed in this paper. The parameter used for comparison is the multicast distribution tree cost, which is built by means of Steiner based algorithms. We measure this parameter by means of an exhaustive simulation campaign by analysing the performance dependence versus the different parameters: device coverage range, number of MANET nodes, multicast group size and mobility model.

Bluetooth is a low-cost, short-range wireless technology capable of providing many communication functionalities, ranging from wire replacement to simple personal area networking. In Bluetooth local networking applications, a critical issue still under study is the evaluation of the network performance when multiple piconets are simultaneously active in the same area, thus, causing mutual interference. We provide a closed-form expression for the packet loss probability in Bluetooth dense piconet area accounting for capture effects due to propagation losses. The effectiveness of the proposed approach is assessed by comparing the analytical results with those obtained from Monte Carlo simulations. By considering different scenarios, we show the dependence of results on the geometry and on the characteristics of the environment. It is observed that packet loss probability can significantly change with the position of the reference receiver in the area, as well as with the extension of the piconets area as compared with the coverage area of the receiver. We use the packet loss probability to evaluate the upper and the lower bounds of the network aggregate throughput and the average packet transmission time. Due to propagation effects, large variations of these parameters with the position of the reference receiver in the area are evidenced.

In this paper, the optical burst switching with burst dropping (OBS/BD) technique is proposed to be implemented in an all-optical backbone network to support IP traffic. The OBS/BD is based on two main features: i) several IP packets are assembled in a single macro-packet, called burst; ii) the burst contention in an optical switch is handled by the means of two techniques: the wavelength dimension and the "burst dropping". In the optical burst switching (OBS), the entire burst is discarded when all of the output wavelengths are engaged at its arrival instant. Whereas, the OBS/BD technique discards only the initial part of the burst and forwards the final part of the burst beginning at the instant in which one wavelength becomes free. Obviously, the OBS/BD, respect to the OBS, allows to increase the switch throughput, i.e. the number of forwarded IP packets. We develop the analytical models that quantify this increase tacking into account of several system parameters.

We study the optical burst switching (OBS) paradigm for the support of the TCP flows in an all optical network (AON). We analyze the TCP send rate, i.e. the amount of data sent per time unit, taking into account of: (i) the burst assembly mechanism, called burstification process; (ii) the burst loss events inside the OBS network. The goals of the paper are to investigate the effect of the variation of the burstification period and to derive some general guidelines about the dimensioning of the burstification period. With respect to the case in which any assembly mechanism is missing, the results show that an accurate dimensioning of the burstification period yields negligible penalties with regard to the low speed sources and significant benefits with regard to the high speed sources.

This paper analyzes a framework to offer reservation of resources and QoS guarantees according to the resource reservation protocol (RSVP) paradigm in a network cloud that supports a differentiated services architecture. The key elements are: intelligent edge devices; a flow admission and resource allocation method involving an admission control server; "simple" core routers based on the differentiated services model. The main functionality of a client/server protocol between the edge devices and the admission control server, called simple admission control protocol, is described. The proposed framework is referred to as admission control server based resource allocation. Scalability is analyzed and compared with RSVP approach.