This paper presents a holistic peer selection scheme in multi-domain environments, aiming to mitigate Peer-to-Peer (P2P) traffic volumes over expensive inter-domain links as well as the maintenance of desirable P2P users' perceived service quality. The mechanism combines the traditional locality-aware peer selection with the consideration of ISP business relationship. By leveraging between the two peering strategies, the risk of possible congestion on critical inter-connected links can be effectively alleviated due to more concentrated P2P traffic over fewer inter-ISP links under pure cooperative peering schemes. According to our analytical modelling, the proposed hybrid approach is able to achieve better performance for P2P users, and can retain desirable network efficiency as of the cooperative peer selection strategy. Our modelling based analysis offers the incentives to perform peer selections in multi-domain environments wherein non-cooperative networks and cooperative networks coexist.

The continuous growth in volume of Internet traffic, including VoIP, IPTV and user-generated content, requires improved routing mechanisms that satisfy the requirements of both the Internet Service Providers (ISPs) that manage the network and the end-users that are the sources and sinks of data. The objectives of these two players are different, since ISPs are typically interested in ensuring optimised network utilisation and high throughput whereas end-users might require a low-delay or a high-bandwidth path. In this paper, we present our UAESR (Utilisation-Aware Edge Selected Routing) algorithm, which aims to satisfy both players' demands concurrently by selecting paths that are a good compromise between the two players' objectives. We demonstrate by simulation that this algorithm allows both actors achieve their goals. The results support our argument that our cooperative approach achieves effective network resource engineering at the same time as offering routing flexibility and good quality of service to end-users.

Social opportunistic networks are intermittently connected mobile ad hoc networks (ICNs) that exploit human mobility to physically carry messages between disconnected parts of the network. Human mobility thus plays an essential role in the performance of forwarding protocols in the networks, and people's movements are in turn affected by their social interactions with each other. In this paper we present an analysis of the traffic distribution among the nodes of social opportunistic networks and its impact on network capacity. For our analysis, we use a human contact graph that represents a social network of individuals. We characterize the graph as a scale-free network and apply forwarding strategies based on the information required by a node to select relays for its messages, categorising this information either as isolated or complete network or local network knowledge. We use a social network property, centrality, for the forwarding strategies, additionally considering tie strength in the forwarding metric and investigate their impact on traffic distribution. We show that all the strategies result in unfair traffic distribution due to a strong non-random structure of the networks, where hub nodes process much more relay traffic than non-hub nodes. Finally, we present a mathematical model of network capacity as an upper-bound of network delivery performance where hub nodes' resources become the limiting factors, and show that including tie strength in the forwarding metric improves the network capacity.

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

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

With the increasing importance of the Internet for delivering personal and business applications, the slow re-convergence after network failure of existing routing protocols becomes a significant problem. This is especially true for real time multimedia services where service disruption cannot be generally tolerated. In order to ensure fast network failure recovery, IP Fast Reroute (FRR) can be adopted to immediately reroute affected customer traffic from the default path onto a backup path when link failure occurs, thus avoiding slow Interior Gateway Protocol (IGP) re-convergence. We notice that IGP link weight setting plays an important role in influencing the protection coverage performance in intra-domain link failures. Therefore in this paper we present an IGP link weight optimization scheme for backup path provisioning, which works on top of a multi-plane enabled routing platform. The scheme aims to optimize the path diversity among multiple routing planes. Due to the large search space of possible intra-domain link weights, in this paper we adopted a global search method based on a Genetic Algorithm to optimize the IGP link weights. Evaluation results show that in most cases a set of optimal link weights can be found which ensures that there are no more critical shared links among all the diverse paths on each routing plane. As a result, backup paths can be always available in case of single link failures.

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

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

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

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

Mobile ad-hoc networks (MANETs) are well known to be vulnerable to various attacks, due to features such as lack of centralized control, dynamic topology, limited physical security and energy constrained operations. In this paper we focus on preventing denial-of-service (DoS) attacks. As an example, we consider intruders that can cause DoS by exploiting the route discovery procedure of reactive routing protocols. We show the unsuitability of tools such as control chart, used in statistical process control (SPC), to detect DoS and propose an anomaly-based intrusion detection system that uses a combination of chi-square test & control chart to first detect intrusion and then identify an intruder. When the intruder is isolated from the network we show reduced overhead and increased throughput. Simulation results show that our algorithm performs well at an affordable processing overhead over the range of scenarios tested.

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

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

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

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

A secure multicast communication is important for applications such as pay-per-view and secure videoconferencing. A key tree approach has been proposed by other authors to distribute the multicast group key in such a way that the rekeying cost scales with the logarithm of the group size for a join or depart request. The efficiency of this key tree approach critically depends on whether the key tree remains balanced over time as members join or depart. In this paper, we present two Merging Algorithms suitable for batch join requests. To additionally handle batch depart requests, we extend these two algorithms to a Batch Balanced Algorithm. Simulation results show that our three algorithms not only maintain a balanced key tree, but their rekeying costs are lower compared with those of existing algorithms.

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

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

Security is an important concern in today's information age and particularly so in satellite systems, where eavesdropping can be easily performed. This paper addresses efficient key management for encrypted multicast traffic transmitted via satellite. We consider the topic of encrypting traffic in large multicast groups, where the group size and dynamics have a significant impact on the network load. We consider life cycle key management costs of a multicast connection, and show for a logical key hierarchy (LKH) how member preregistration and periodic admission reduces the initialization cost, and how the optimum outdegree of a hierarchical tree varies with the expected member volatility and rekey factor. This improves network utilization, but encryption at the network layer can pose problems on satellite links. We, therefore, propose and analyze an interworking solution between multilayer Internet protocol security (IPSEC) and LKH that also reduces key management traffic while enabling interworking with performance enhancing modules used on satellite links.