Effective spectrum sharing requires a nuanced understanding of how radio activity varies not only across frequency and geography but also with altitude, an increasingly important dimension for drone networks and non-terrestrial systems. This paper presents a comprehensive survey of existing spectrum measurement studies in the sub-6 GHz range, identifying major gaps in coverage, such as limited measurements involving altitude variation, a lack of longitudinal datasets, and the absence of publicly available geotagged aerial data. To address these limitations, we conduct a multi-year spectrum monitoring campaign using an aerial platform equipped with software-defined radios (SDRs), operating in both urban and rural areas of Raleigh, NC, USA. The aerial platform enables high-resolution measurements of spectrum activity from the ground up to 300 m. We analyze occupancy patterns across licensed and unlicensed bands, including Long Term Evolution (LTE), 5G (New Radio) (NR), and Industrial, Scientific, and Medical (ISM) bands, and document year-over-year changes that reflect evolving commercial deployments and regulatory trends. We further perform an altitude-dependent analysis of spectrum occupancy and received power across the 89 MHz–6 GHz range, highlighting how three-dimensional measurement perspectives reveal usage patterns that are not observable from ground-level sensing alone. Our results demonstrate that altitude is a critical dimension for spectrum characterization and should be considered in future spectrum policy, sensing strategies, and system design. This study provides both a literature-based and measurement-based foundation for altitude-aware spectrum analytics, supported by a publicly available geotagged dataset to enable reproducible research for emerging aerial networks and non-terrestrial communication systems.

Reliable connectivity is essential to integrate UAVs into the National Airspace System (NAS) and enable beyond-visual line-of-sight (BVLOS) operations. Due to existing infrastructure and capabilities, cellular technologies can potentially serve the connectivity requirements for UAVs. The field studies show that existing cellular networks provide poor coverage at higher altitudes, and hence, many solutions have been proposed to improve aerial coverage. In this work, we assume that base stations can temporarily improve the service and provide multiple service options to the UAVs at some associated costs. We propose a trajectory planning algorithm that considers the adaptive bitrate requirements of an application and all the service options available to find the optimal path between points in the 3D space. The algorithm aims to balance between path length and path cost.

UAVs are increasingly used in various applications, and some can adapt to varying radio conditions. In the future, UAVs from different vendors will share the air space deployed for different operations, and hence, maintaining minimum connectivity will become crucial for traffic management and beyond visual line-of-sight (BVLOS) safe operations. As the aerial coverage is fragmented, trajectory planning for UAVs while maintaining basic connectivity becomes challenging. In this work, we propose a trajectory planning algorithm that uses the weighted sum method to measure and compare the paths based on the distance, coverage conditions, and adaptable network requirements. We further analyze the impact of movements a UAV can make in 3D grid for pathfinding. A UAV can move in different directions at variable distances. Our results show that a higher degree of movement allows the algorithm to find shorter paths than the lower degree of movement. However, the runtime depends upon the coverage conditions.

Peer-to-peer (P2P) botnets use decentralized command and control networks that make them resilient to disruptions. The P2P botnet overlay networks manifest structures in mutual-contact graphs, also called communication graphs, formed using network traffic information. It has been shown that these structures can be detected using community detection techniques from graph theory. These previous works, however, treat the communication graphs and the P2P botnet structures as static. In reality, communication graphs are dynamic as they represent the continuously changing network traffic flows. Similarly, the P2P botnets also evolve with time, as new bots join and existing bots leave either temporarily or permanently. In this paper we address the problem of detecting such evolving P2P botnet communities in dynamic communication graphs. We propose a reinforcement-based approach, suitable for large communication graphs, that improves precision and recall of P2P botnet community detection in dynamic communication graphs.

The deployment at scale of Unmanned Aerial Systems have become increasingly imminent in the last few years, even as concerns regarding the dependability and predictability of their command and control channels remain fully to be addressed. The intersection of ground-to-air wireless communications, aerial networking, and trajectory control has become a research area of sharp interest. The validation of such research, beyond the theoretical/simulation stage, requires a facility that is both realistic, and admits of potentially risky or unsafe operation, while in the end guaranteeing personnel and equipment safety. The AERPAW project is an ambitious project, funded by the PAWR program of the US NSF, to create a remote accessible research platform for a research facility to enable such validation. To enable remote usage of such a testbed, yet provide the researcher with complete experimental freedom, the AERPAW facility includes a combination of architectural mechanisms that balance freedom of experimentation with regulatory compliance and safety. In this paper, we articulate the challenges and considerations of designing such mechanisms, and present the architectural features of AERPAW that attempt to realize these lofty goals.

Internet of Things (IoT) is an intelligent infrastructure and service technology that connects objects to people for monitoring and control. The number of IoT devices is rapidly increasing in various environments. Although the DNS protocol is being applied to IoT networks to create unique identifiers, it is burdensome for users to manually create and configure a globally unique name for each device. DNS Name Autoconfiguration (DNSNA) was proposed to register the DNS name of IoT devices automatically and utilize IoT devices globally. However, DNSNA without secure authentication and authorization leads to potential threats, such as the registration of malicious IoT devices, and other IoT security attacks. In this paper, we propose an Advanced Secure DNS name autoconfiguration with Authentication and Authorization for enterprise IoT network (ASDAI). Especially, we provide the first model using the convergence of extended OAuth 2.0 and Kerberos v5. The proposed protocol supports (1) reliable device / administrator registration, (2) secure DNS name autoconfiguration, and (3) user / service authentication and authorization procedure for the heterogeneity and scalability of enterprise IoT networks.

Software defined networking (SDN) allows organizations to modify networks programmatically to implement custom forwarding behavior and to react to changing conditions. While there are many approaches available to implement SDN those that leverage forwarding table abstractions such as OpenFlow and P4 require developers to decompose problems into one or more tables associated with a definable pipeline. This paper explores tradeoffs between table depth and pipeline length associated with different problem decomposition options by analyzing the performance impact on hardware and software data planes including software data planes leveraging hardware acceleration through the use of SmartNICs.

Large botnets have enormous combined computation and network resources which can be used to launch powerful attacks. Botnets that use peer-to-peer (P2P) command & control (C&C) overlay networks have emerged to make themselves resilient against detection and disabling of individual bots. In a communication graph with network nodes represented by vertices and network traffic between the nodes represented by edges, the P2P botnet C&C traffic can reveal community structures. Detecting communities in a graph is a well studied problem in literature, and several algorithms have been proposed based on various approaches. Previous works have proposed detecting P2P botnets using various community detection algorithms, though in general they suffer from low precision. We propose BotCLAM, an algorithm to detect P2P botnet community structures in a communication graph, based on the differing definitions of community offered by modularity and strong community. Combining the speed and coverage of modularity optimization algorithms with label propagation approach that finds smaller but strong communities, our algorithm detects P2P communities with improved precision (65% - 75%) while matching the recall (>98%) of modularity optimization.

Routing protocols, including OSPF, are essential for correct network function and therefore attractive targets for attackers. Many attacks on OSPF are known. Limited progress on detection and prevention has meant that protecting against and recovering from such attacks typically requires significant manual effort. The goal of this research is to make networks more resilient to all known attacks that exploit OSPF Link State Advertisements (LSAs), without requiring modifications to the OSPF protocol. The proposed solution adds a Virtual Routing Resilience Cluster (VRRC) to the network infrastructure. This cluster makes use of three concepts. The first is that new links are added infrequently to networks. By comparing with previous topology information, suspect LSA information can be detected and rejected. The second is that it should be possible to corroborate LSAs by comparing with data made available from other layers of the network. LSAs that conflict with data from other layers can safely be rejected. The third is a rudimentary recovery and adaptation system designed to reestablish network connectivity and prevent the attack from happening again. This can be accomplished by purging the routing table and generating routing policies to block the offending source of the attack. We show that these concepts lead to protection against all known OSPF attacks, and that the concepts are feasible to implement, without resorting to the complexity of key management, and without modifying the routing protocol. The ability of the network to reconfigure around normal routing failures is also not compromised. A VRRC was added to a testbed consisting of standard routers, and shown to provide protection against state of the art attacks. The impact of the implementation on network throughput and router CPU usage is shown.

New use cases for advanced wireless technologies are emerging in the unmanned aerial systems (UAS) spaces. These put pressure on technology and regulation. The way to overcome this is to gain experience and collect data while operating UAS in production environments. To this end, we introduce AERPAW: Aerial Experimentation and Research Platform for Advanced Wireless, and present an architecture for designing a large-scale community testbed in a production-like environment to enable controllable experiments with latest wireless technologies and systems. Using advanced networking and virtualization technology to manage the platform resources, users will be able to configure the testbed for running a variety of at-scale experiments for UAS localization and tracking, networking, trajectory optimization, spectrum management, and aerial-terrestrial cellular network design and optimization based on 5G and software radio technology, among others.

Botnets can be used to launch large scale and expensive attacks. Botnets are also difficult to detect and disable, especially when they use peer-to-peer (P2P) command & control structures. In this paper we propose GADFly - a fast and robust algorithm to detect P2P botnet structures in communication graphs built from network flow meta-data. While other algorithms have been proposed in literature that use graph analysis or machine learning techniques to detect botnets, they are either slow or have impractical false positives for realistically large graphs with millions of nodes. They also assume availability of universal communication graph data, which is not realistic. The method proposed here is able to precisely detect P2P botnet structures with extremely low false positive rates. In addition, GADFly is also very fast and robust in the face of gaps in communication graph data, making it suitable for practical deployments.

The routing infrastructure of the Internet is a high-value target for malicious actors. The Open Shortest Path First (OSPF) protocol is one of the most widely used protocols for Autonomous System (AS) internal routing, and has been the subject of attacks targeted at partitioning the network. Because of the widespread existing penetration of OSPF, research in defending against such attacks has focused toward prevention and detection techniques working in tandem with OSPF routers, rather than attempted modification of the protocol itself. However, comparatively few studies have attempted to address the topic of a network capable of recovery, which signifies a system that can be proof to an attack without the necessity for any specific attack to be explicitly detected, localized, or countered. In this paper, we first examine these existing recovery techniques, and come up with the underlying common mechanisms that they utilize. Then we examine the continued usefulness of these approaches with the more modern persistent OSPF attacks, by running actual attacks against an isolated network formed of typical commercial network elements, while allowing each such recovery mechanism to defend the network. Our experiments show that three of the five basic mechanisms can no longer defend against partitioning attacks when attacks are persistent, and provides relevant performance results for the other two. Our results also point the way to further improving these mechanisms for even more sophisticated attacks, in the future.

In this paper, we investigate the effect of which different pricing algorithms have on a flexible optical choice-based network. Our pricing algorithms attempts to perform proactive collaborative optimization by offering some network service choice, as more attractive than others, and thus encourage users to buy services that are in surplus instead of those which use resources that are viewed more precious due to their scarcity. We evaluate these pricing algorithm's performance on the system by analyzing the impact on the network utilization, customer utilization, and the generated revenue.

In various resource sharing networks, opportunistic resources with dynamic quality are often present for the users to exploit. As many user tasks are delay-tolerant, this favorably allows the network users to wait for and access the opportunistic resource at the time of its best quality. For such delay-tolerant and opportunistic resource sharing networks, the resource accessing strategies developed in the literature suffer from three limitations. First, they mainly focused on single-user scenarios, whereas the competition from other users is ignored. Second, the influence from the resource seller who may take actions to manipulate the resource sharing procedure is not considered. Third, the impact of the actions from both the network users and the resource seller on the resource quality dynamics is not considered either. To overcome these limitations, a leader-follower controlled Markov stopping game (LF-C-MSG) is developed in this paper. The derived Stackelberg equilibrium strategy of the LF-C-MSG can be used to guide the behaviors of both the network users and the resource seller for better performance and resource utilization efficiency. Two exemplary applications of the proposed LF-C-MSG are presented, along with corresponding numerical results to verify the effectiveness of the proposed framework.

Opportunistic resources are often present in various resource sharing networks for the users to exploit, but their qualities often change over time. Fortunately, many user tasks are delay-tolerant, which offers the network users a favorable degree of freedom in waiting for and accessing the opportunistic resource at the time of its best quality. For such delay-tolerant and opportunistic resource sharing networks (DT-ORS-Net), the corresponding optimal accessing strategies developed in existing literature mainly focus on the single-user scenarios, while the potential competition from other peer users in practical multi-user DT-ORS-Net is often ignored. Considering this, a multi-player Markov stopping game (M-MSG) is developed in this work, and the derived Nash equilibrium (NE) strategy of this M-MSG can guide network users to properly handle the potential competition from other peers and thus exploit the time diversity of the opportunistic resource more effectively, which in turn further improves the resource utilization efficiency. Applications in the cloud-computing and the mobile crowdsourcing networks are demonstrated to verify the effectiveness of the proposed method, and simulation results show that using the NE strategy of the proposed M-MSG can provide substantial performance gain as compared to using the conventional single-user optimal one.

Zero-determinant (ZD) strategies that allow a player to unilaterally control the linear combinations of its own and other players' expected rewards in iterated games have recently found wide applications. However, existing ZD strategies mainly focus on some specific scenarios with restrictions on the number of players or actions a player can take. Targeting wider applications and better performance, the ZD strategies along with corresponding existence conditions for general multi-player multi-action iterated games are developed in this work, including existing ones as special cases. In addition, an interesting fact that every player can have at most one master player (that can control the expected reward of the given player) is revealed.

Motivated by information-theoretic security, link signature (LS)-based security mechanisms exploit the ample channel characteristics between wireless devices for security establishment. Nevertheless, LS is originated from wireless environments and hence may exhibit potential vulnerabilities that can be exploited by adversary in the vicinity. As to this, it is widely believed in existing literature on LS that, a half-wavelength guard zone is sufficient to decorrelate the adversary channel from the legitimate one and thereby secures the legitimate LS. However, such an assumption may not hold universally - in some environments, high channel correlations have been observed for much larger spatial separations. Considering this, a comprehensive understanding of channel correlation in different wireless environments is needed for more confident deployment of LS-based security mechanisms. To this end, various well-established channel correlation models are investigated in this work. A set of important physical factors that have significant influence on LS security are identified, and with the obtained insights, extensive simulations are conducted to explore suitable guard zone sizes for LS in several typical indoor and outdoor environments. Experimental results based on universal software radio peripheral (USRP) platforms and GNURadio are also presented to further support the analysis.

Intrusion detection systems (IDSs) assume increasingly importance in past decades as information systems become ubiquitous. Despite the abundance of intrusion detection algorithms developed so far, there is still no single detection algorithm or procedure that can catch all possible intrusions; also, simultaneously running all these algorithms may not be feasible for practical IDSs due to resource limitation. For these reasons, effective IDS configuration becomes crucial for real-time intrusion detection. However, the uncertainty in the intruder's type and the (often unknown) dynamics involved with the target system pose challenges to IDS configuration. Considering these challenges, the IDS configuration problem is formulated as an incomplete information stochastic game in this work, and a new algorithm, Bayesian Nash-Q learning, that combines conventional reinforcement learning with a Bayesian type identification procedure is proposed. Numerical results show that the proposed algorithm can identify the intruder's type with high fidelity and provide effective configuration.

Deployment of innovative new networking services requires support by network providers. Since economic motivation plays an important role for network providers, it is critical that a network architecture intrinsically considers economic relationships. We present the design of a protocol that associates access to network services with economic contracts. We show how this protocol can be realized in fundamentally different ways, using out-of-band signaling and in-band signaling, based on two different prototype implementations. We present results that show the effectiveness of the proposed protocol and thus demonstrate a first step toward realizing an economy plane for the Internet.

To ensure continuous functioning and satisfactory performance, a wireless communication system has to not only learn and adapt to the unknown and ever-changing wireless environment, but also strategically deal with the usually unfamiliar peers. Incomplete information stochastic game (SG) is a promising model for the corresponding analysis and strategy design. In this work, an exemplary multi-channel spectrum access game (SAG) with unknown environment dynamics and limited information of the other player is considered to illustrate the proposed solution for the corresponding incomplete information SG. To find the best communication strategy in the face of uncertainty, a joint reinforcement learning and type identification algorithm is developed, which is provably convergent under certain technical conditions. Numerical results show that using the proposed algorithm, a wireless user can gradually achieve the same performance as that in the corresponding complete information game.

It is understood from past decade of research that a wireless multi-hop network can achieve maximum network throughput only when its nodes operate at a minimum common transmission power level that ensures network connectivity (availability). This point of optimality where maximum availability and throughput is guaranteed in an interference-optimal network has been the basis of numerous design problems in wireless networks. In this paper, we claim that when performability (availability weighted performance) is considered as opposed to average case throughput performance, there does not exist a transmission power (or node density) that can maximize both availability and performability. Since the current mesh networks are expected to deliver carrier-grade services to its users, the availability-performability tradeoff presented in this paper holds a special importance. While availability metric is a necessary one for any networking system intended to provide continuous service, past research has shown a strong correlation between performability and quality of user experience in case of wireless networks. The contributions of the paper are as follows: (1) We first define availability and performability in the context of wireless mesh networks, and then develop efficient algorithms on the basis of intelligent state sampling that can calculate both the quantities with reasonable accuracy. (2) We apply the evaluation methods to two existing mesh networks (GoogleWiFi and PoncaCityMesh) to demonstrate that their current design can not guarantee a reasonable level of availability or performability. (3) Using hundreds of hours of simulations, we analyze the impact of two basic deployment factors (node density and transmission power) on availability and performability. We outline numerous novel results that emerge due to joint availability-performability analysis including the observation about availability-performability tradeoff.

The problem of providing an agile, energy-aware, flexible optical network architecture is one of the challenges in optical networking in the coming decade. A key element in this challenge is the balancing of the benefits to customer and provider, and creating an agile system capable of reflecting both provider and customer interests on an ongoing basis as network conditions change. In this paper, we articulate how the traditional optical networking research area of traffic grooming may be combined with recent advances in Internet architecture, specifically a proposed Future Internet architecture called ChoiceNet, to make some key contributions to this problem. Our basic premise is that a marketplace that allows providers to advertise services on a dynamic basis, with accompanying prices that reflect the relative resource scarcity in the network at the time, provides a rendezvous of customer and provider interests, allowing collaborative optimization of network resource usage. With these pre-announced information, customers are able to make informed choices, thus participating in optimizing the use of available network resources for win-win benefits for providers and customers. We show how such marketplace choices naturally arise for energy-aware optical networks, and investigate the ensuing customer-provider interactions. Our results demonstrate the potential for win-win in this approach.

Wireless multihop networks such as ad hoc and mesh networks are susceptible to both random uncertainty of radio links and malicious jamming. Traditional unipath routing techniques reduce the overall packet delivery ratio in presence of network failures. Being able to predict the reliability of a transmission a priori can be useful in designing reliable networks. We consider a network of nodes addressed by their locations carrying out redundancy-based routing, and propose an analytical model that can predict the reliability of a transmission given certain parameters such as network node density and region of network involved in the transmission. For this study we consider a geo-diffuse multipath routing technique called Petal routing, which takes advantage of the broadcast nature of wireless networks to reduce the number of transmissions for multiple paths. We investigate the accuracy of the analytical model by comparing metrics such as reliability obtained from the model and from OPNET simulations.

Wireless multihop networks have a wide variety of applications, due to their rapid deployment times and minimal configuration requirements. Transmissions in wireless networks may require performance guarantees, which can be achieved by using advanced routing strategies. We examine one such performance metric, namely reliability, or packet delivery ratio in a failure-prone wireless network. We use control theoretic methods to obtain an understanding of routing in wireless multihop networks. In particular, we model ad hoc wireless networks as stochastic dynamical systems where, as a base case, a centralized controller pre-computes optimal paths to the destination. This technique can be used to obtain the highest achievable reliability for a given transmission. We compare this approach with the reliability achieved by some of the widely used routing techniques in multihop networks. We also propose extensions to the base case that can be more applicable to practical scenarios. Results show that our approach can be used to theoretically characterize reliability of end-to-end transmissions in wireless networks.

Software Defined Networking (SDN) offers traffic characterization and resource allocation policies to change dynamically, while avoiding the obsolescence of specialized forwarding equipment. Open Flow, a SDN standard, is currently the only standard that explicitly focuses on multi-vendor openness. Unfortunately, it only provides for traffic engineering on an integrated basis for L2-L4. The obvious approaches to expand Open Flow's reach to L7, would be to enhance the data path flow table, or to utilize the controller for deep packet inspection, both introduces significant scalability barriers. We propose and prototype an enhancement to Open Flow based on the idea of an External Processing Box (EPB) optionally attached to forwarding engines, however, we use existing protocol extension constructs to control the EPB as an integrated part of the Open Flow data path. This provides network operators with the ability to use L7-based policies to control service insertion and traffic steering, without breaking the open paradigm. This novel yet eminently practical augmentation of Open Flow provides added value critical for realistic networking practice. Retention of multi-vendor openness for such an approach has not been previously reported in literature to the best of our knowledge. We report numerical results from our prototype, characterizing the performance and practicality of this prototype by implementing a video reconditioning application on this platform.

In this paper, we propose a service architecture for verification, a necessary component of a choice-based economy architecture of the future Internet. Such a verification architecture motivates and addresses the task of enabling users to verify, or obtain third-party verification of, whether the service components offered by various network service providers were responsible for meeting or failing to meet overall service expectations. To be useful, such an architecture must allow viable business propositions for each of the principals, and provide meaningful results at reasonable cost and overhead. We articulate the architectural decisions, requirements, roles and interfaces. We then describe a proof-of-concept prototype realized in NS- 3. Finally, we make observations contrasting our results with previous approaches and discuss the implementation challenges to realize this work in practice.

With recent advances in Software-defined Radios (SDRs), it has indeed became feasible to dynamically adapt the channel widths at smaller time scales. Even though the advantages of varying channel width (e.g. higher link throughput with higher width) have been explored before, as with most of the physical layer settings (rate, transmission power etc.), naively configuring channel widths of links can in fact have negative impact on wireless network performance. In this paper, we design a cross-layer channel width assignment scheme that adapts the width according to the backlog of link-layer queues. We leverage the benefits of varying channel widths while adhering to the invariants of back-pressure utility maximization framework. The presented scheme not only guarantees improved throughput and network utilization but also ensures bounded buffer occupancy and fairness.

There has been a great interest in defining a new network architecture that can meet the needs of a future Internet. One of the main challenges in this context is how to realize the many different technical solutions that have developed in recent years in a single coherent architecture. In addition, it is necessary to consider how to ensure economic viability of architecture solutions. In this work, we discuss how to design a network architecture where choices at different layers of the protocol stack are explicitly exposed to users. This approach ensures that innovative technical solutions can be used and rewarded, which is essential to encourage wide deployment of this architecture.

The back-pressure based scheduling policy originally proposed by Tassiulas et al. in [1] has shown the potential of solving many fairness and network utilization related problems of wireless multi-hop networks. Recently, the scheduling policy has been adapted in random medium access protocols such as CSMA/CA using prioritization of MAC layer transmissions. Here, MAC priorities are used to provide differentiated services to nodes depending on their queue backlogs. Even though these schemes work well in experiments to emulate back-pressure scheduling, they perform poorly with realistic Internet-type traffic where there is a large variation in packet sizes. In this paper, we propose packet aggregation based back-pressure scheduling which aggressively increases the rates at which back-logged queues are served. Different from other aggregation schemes, the presented scheme utilizes the back-pressure principles for determining when and how much aggregation is performed. We show that this results into increased service rates of back-logged queues which in turn results into high network throughput and utilization. We verify our scheme using simulations and testbed experiments, and show that it achieves significant performance improvements as compared to the original scheme.

Optical networks are widely used in communication systems. Finding optimal converter placement for broadcast on optical networks has been an important area of research. In this problem, the free wavelengths on different links of a optical network are used to support network-wide broadcast, which is useful as a control channel or other OAM tasks. Previous work has articulated the essential difficulty of this problem. In this work, we recognize that bandwidth minimization is not an appropriate goal for this problem, and by using multiple wavelengths, and replicating some transmissions, it is possible to reduce the number of converters. We show example schemas to show that the difference in the optimal number of converters can be arbitrarily large, that adopting multiple wavelength paths whose union contains cycles can strictly reduce the optimal number, and then present a heuristic algorithm for broadcast path assignment to minimize converters under the new model.

Ad hoc wireless networks are characterized by frequent node mobility, limited power reserves and interfering transmissions. On-demand routing proves to be more successful in such networks, as it reduces the traffic overhead of sending periodic updates, but they may be susceptible to both random uncertainty in radio links, and malicious jamming. We consider a network of nodes addressed by their locations, and propose a novel routing technique that we call Petal Routing, which maximizes reliability by using pathsets, made of diverse multiple paths, in place of a single path. Petal Routing takes advantage of the broadcast nature of wireless networks to reduce the number of transmissions for multiple paths by overlapping the multiple diverse paths. Various tunable parameters built into the approach can be used to improve metrics such as delay, number of transmissions and packet delivery ratio. We evaluate the performance of our scheme using extensive simulations, and show that it is viable.

In this paper, we consider power control as network layer problem in wireless mesh networks. The network connectivity between nodes is determined by their communication range which in turn can be controlled by adjusting the transmit power level. It is generally acknowledged that reducing transmit power levels of nodes to the minimum required to retain connectivity always increases network capacity. In this work, we show that though this is true for CSMA/CA based medium access, increasing power level of nodes can be beneficial in many cases when links are TDM-scheduled. Based on analysis and simulations, it is observed that increasing power levels of nodes (and decreasing number of hops in routing paths) results in increase of throughput in many representative traffic patterns and topologies. We characterize achievable spatial reuse and capacity with respect to power control in different topologies and traffic patterns. With increasing number of MAC protocols adopting TDMA approach, results presented here can be crucial in understanding how capacity is affected with varying levels of network connectivity.

Wireless networks are susceptible to localized disruptions, due to the shared nature of the medium. Radio jamming, the most common type of localized disruption causes wireless link failures. Jamming mitigation has been traditionally addressed in the physical and MAC layers. Such approaches come with added complexity and often require specialized hardware. We investigate whether a generally applicable routing layer approach, based on multipath routing coupled with power control, can mitigate the effects of jamming. We propose (1) proactive protection and (2) reactive protection techniques for jamming mitigation in wireless multihop networks with fixed nodes. For reactive protection, we propose a distributed geographic routing algorithm that finds alternative route to the destination, starting from the first node with failed link on the original path. We evaluate the performance of this algorithm using OPNET simulations.

When shortest path routing is employed in large scale multi-hop wireless networks, nodes located near the center of the network have to perform disproportionate amount of relaying for others. To solve the problem, various divergent routing schemes are used which route the data on center-avoiding divergent routing paths. Though they achieve better load balancing, overall relaying is increased significantly due to their longer routing paths. In this paper, we propose power control as a way for balancing relay load and mitigating hot-spots in wireless networks. Using a heuristic based on the concept of centrality, we show that if we increase the power levels of only the nodes which are expected to relay more packets, significant relay load balancing can be achieved even with shortest path routing. Different from divergent routing schemes, such load balancing strategy is applicable to any arbitrary topology. Also, it is shown that centrality based power control results into better throughput capacity in many different topologies.

When shortest path routing is employed in large scale multi-hop wireless networks, nodes located near the center of the network have to perform disproportional amount of relaying for others. In energy-constrained networks like sensor, such unfair forwarding results into early depletion of batteries of these congested nodes. To solve the problem, various divergent routing schemes are used which route the data on center-avoiding divergent routing paths. Though they achieve better load balancing, overall relaying is increased significantly due to their longer routing paths which in turn results into reduced energy efficiency. In this paper, we propose power control as a way of achieving better load balancing in multi-hop wireless networks. We show that when communication range of nodes are properly controlled using power control, better load balancing can be achieved using shortest paths only. Such a strategy also decreases overall relaying in the network when compared to divergent routing schemes. We use the concept of centrality to achieve appropriate balance between relay burden of nodes and their power levels. Numerical results confirm that centrality based load balancing significantly improves network lifetime of sensor networks.

In recent years, Internet Protocol (IP) telephony has been a real alternative to the traditional public switched telephone networks (PSTN). IP telephony offers more flexibility in the implementation of new features and services. The session initiation protocol (SIP) is becoming a popular signaling protocol for Voice over IP (VoIP) based applications. The SIP proxy server is a software application that provides call routing services by parsing and forwarding all the incoming SIP packets in an IP telephony network. The efficiency of this process can create large scale, highly reliable packet voice networks for service providers and enterprises. We established that the efficient design and implementation of the SIP proxy server architecture can enhance the performance characteristics of a SIP proxy server significantly. Since SIP proxy server performance can be characterized by its transaction states of each SIP session, we emulated the M/M/l performance model of the SIP proxy server and studied some of the key performance benchmarks such as average response time to process the SIP calls and mean number of SIP calls in the system. We showed its limitations, and then studied an alternative M/M/c based SIP proxy server performance model with enhanced performance and predictable results.

We present a hierarchical algorithm for grooming lightpaths into wavebands, and routing wavebands over a network of multigranular switching nodes. This algorithm focuses on lowering the number of wavelengths W and ports over the network while being conceptually simple, scalable, and consistent with the way networks are operated and controlled in practice. Our experiments indicate that this algorithm easily scales across different waveband and network sizes.

The design of the SILO network architecture of fine-grain services was based on three fundamental principles. First, SILO generalizes the concept of layering and decouples layers from services, making it possible to introduce easily new functionality and innovations into the architecture. Second, cross-layer interactions are explicitly supported by extending the definition of a service to include control interfaces that can be tuned externally so as to modify the behavior of the service. The third principle is ldquodesign for change:ldquo the architecture does not dictate the services to be implemented, but provides mechanisms to introduce new services and compose them to perform specific communication tasks. In this paper, we provide an update on the current status of the architecture and the prototype software implementation. We also introduce the concept of ldquosoftware defined opticsrdquo (SDO) to refer to the emerging intelligent and programmable optical layer. We then explain how the SILO architecture may enable the rapid adoption of SDO functionality as well as evolving optical switching models, in particular, optical burst switching (OBS).

We propose a new internetworking architecture that represents a departure from current philosophy and practice, as a contribution to the ongoing debate regarding the future Internet. Building upon our experience with the design and prototyping of the just-in-time protocol suite, we outline a framework consisting of (1) building blocks of fine-grain functionality, (2) explicit support for combining elemental blocks to accomplish highly configurable complex communication tasks, and (3) control elements to facilitate (what is currently referred to as) cross-layer interactions. In this position paper, we take a holistic view of network design, allowing applications to work synergistically with the network architecture and physical layers to select the most appropriate functional blocks and tune their behavior so as to meet the application's needs within resource availability constraints. The proposed architecture is flexible and extensible so as to foster innovation and accommodate change, it supports a unified Internet, it allows for the integration of security and management features at any point in (what is now referred to as) the networking stack, and it is positioned to take advantage of hardware-based performance-enhancing techniques.

While research on cross-layer network optimization has been progressing, useful implementations have been lagging because the current Internet architecture does not accommodate cross-layering gracefully. As part of our FIND project, we propose a software architecture for the future Internet that is designed to accommodate such interactions. We present a conceptual overview as well as high level software design and an early prototype implementation, and point out the strengths of our architecture.

Vehicular networks are emerging as an exciting new area of pervasive networking. Roadway congestion amelioration is one of the attractive applications of such a network. The mobility of vehicles on the roadway has been modeled in literature, but the effect of the communication network on the mobility patterns has not been addressed so far. We present such a model of the mobility that integrates the effects of the network. Our model is based on an earlier model using a Enskog dense gas modeling of the traffic flow. Our solutions show that the model is realistic and numerical simulations also verify the results. We also note that this application can cause oscillation waves in the traffic flow, which have so far not been recognized in literature.

Wavelength converters simplify the wavelength assignment problem in virtual topology design in optical networks and increase the utilization of the fiber bandwidth. However, converters are costly, and minimizing the number of converters needed to support a given level of functionality has been investigated in the literature in various contexts. In particular, previous work has addressed the problem of minimizing the number of converters needed to support broadcast over all network nodes with a given set of residual wavelengths on each link. In this paper, we show that previous work leaves the computational complexity of this question open. We go on to show that the problem is in fact NP-complete, but becomes tractable in the special case when the network graph is a tree. We also show that there are cases when the heuristics articulated in previous work fail to provide solutions, and provide some heuristic approaches to solve the general problem.

Optical networks with wavelength routing are expected to form the backbone in the next generation wide area networks. The traffic grooming problem in optical networks is an optimization problem of aggregating sub-wavelength traffic demands onto lightpaths such that the required electronic switching capability, hence network cost, can be minimized. In this paper, we propose an over-provisioning scheme, which pre-allocates the spare capacity of lightpaths to dynamic subwavelength traffic demands such that the network can be more agile in responding to traffic increment requests. For the single-link case, the problem is a convex non-linear programming problem. We provide an exact algorithm to find the optimal solution. The problem with general topologies is then studied. We prove the NP-hardness in this case, and propose heuristics. Numerical results show our heuristics perform well.

Wireless mesh networks are emerging as the next important arena for multihop wireless networking research. Due to several characteristics of these networks, they are amenable to network capacity and resource design in the same manner as more traditional wired networks, with the important difference that wireless interference must be accounted for in design. Studies have already appeared in the literature on such network design. In this paper, we consider this design problem. We mention previous formulations, which address the binary model of interference. We then consider the physical additive interference model, which is the physically more realistic one. So far in literature, the additive nature of interference has been ignored in this context for simplification. We show that existing techniques are not sufficient to address this case, and go on to present a new technique, utilizing blossom inequalities, which can find solutions to this problem. Numerical results show that our approach provides good results in practice.

We consider the problem of traffic grooming in WDM path, star, and tree networks. Traffic grooming is a variant of the well-known logical topology design, and is concerned with the development of techniques for combining low speed traffic components onto high speed channels in order to minimize network cost. Our contribution is two-fold. In the first part of the paper we present a wealth of results which settle the complexity of traffic grooming in path and star networks, by proving that a number of variants of the problem are computationally intractable. Since routing and wavelength assignment in these two topologies is trivial, these results demonstrate that traffic grooming is itself an inherently difficult problem. Our results have implications for ring and other more general topologies, which we explore. In the second part we design practical grooming algorithms with provable properties. Specifically, for all three topologies, we obtain a series of lower and upper bounds which are increasingly tighter but have considerably higher computational requirements; the series of upper bounds forms an algorithm for the traffic grooming problem with strong performance guarantees. We also present corresponding heuristics with good performance. Our work is a first step towards a formal and systematic approach to the grooming problem in general topologies that builds upon results and algorithms for more elementary networks

We present a framework for hierarchical traffic grooming in mesh networks with the objective of minimizing the total number of electronic ports. At the first level of hierarchy, we decompose the network into clusters and designate one node in each cluster as the hub for grooming traffic. At the second level, the hubs form another cluster for grooming inter-cluster traffic. We view each (first- or second-level) cluster as a virtual star, and we present an efficient near-optimal algorithm for determining the logical topology of lightpaths to carry the traffic within each cluster. Routing and wavelength assignment is then performed directly on the underlying physical topology. Our approach scales to large network sizes, and facilitates the control and management of multigranular networks. Comparisons to lower bounds indicate that it is also efficient in its use of the network resources of interest, namely, electronic ports and wavelengths.

Advances in optical data transmission and optical signal routing have caused wide expectation for optical networks to form tomorrow's backbone transport. One attractive feature of these networks is the ability to reconfigure the logical topology of the network seen by higher layers with comparative ease and speed by reconfiguring optical switches, without the need to modify the physical topology of the network. On the other hand, with the current mismatch of bandwidth available from individual wavelength channels and typical bandwidth demands, it is also widely recognized that grooming of subwavelength traffic into the full-wavelength channels is an indispensable component of optical network design. The topic of reconfiguration in optical networks that carry subwavelength traffic has received comparatively little attention. In this paper, we consider this problem. Our main contributions are as follows. We discuss the common basis on which grooming effectiveness and reconfiguration efficiency can be considered, and develop a reconfiguration cost function in keeping with this consideration. We formulate the joint problem of reconfiguration and grooming precisely, and offer a heuristic as well as an exact solution method to solve this problem. In offering numerical simulation results for our algorithms, we make the important observation that a disjoint sequential consideration of the two problems leads to solutions that are very inefficient in the joint sense.

Wireless sensor networks are poised to revolutionize our abilities in sensing and controlling our environment. Power conservation is a primary research concern for these networks. Often, the single most important savings can be obtained by switching off the wireless receiver when not needed. In this paper, we describe an algorithm which allows the nodes to learn the behavior of each other by only observing the transmission behaviors, and from this derive the schedule without external help. Our approach is robust to statistical variations in the nodal transmission periods. We draw important conclusions on the effect of quasi-periodicity on the scalability of the solution. We provide results of numerical simulations that show the effectiveness of our approach.

No abstract available.

We consider the problem of designing a virtual topology to minimize electronic routing, that is, grooming traffic, in wavelength routed optical rings. The full virtual topology design problem is NP-hard even in the restricted case where the physical topology is a ring, and various heuristics have been proposed in the literature for obtaining good solutions, usually for different classes of problem instances. We present a new framework which can be used to evaluate the performance of heuristics and which requires significantly less computation than evaluating the optimal solution. This framework is based on a general formulation of the virtual topology problem, and it consists of a sequence of bounds, both upper and lower, in which each successive bound is at least as strong as the previous one. The successive bounds take larger amounts of computation to evaluate, and the number of bounds to be evaluated for a given problem instance is only limited by the computational power available. The bounds are based on decomposing the ring into sets of nodes arranged in a path and adopting the locally optimal topology within each set. While we only consider the objective of minimizing electronic routing in this paper, our approach to obtaining the sequence of bounds can be applied to many virtual topology problems on rings. The upper bounds we obtain also provide a useful series of heuristic solutions.