An Efficient Hybrid Channel Assignment Protocol for a Multi Interface Wireless Mesh Network

ABSTRACT: In Both multi-interface and dynamicchannel adjustment are prevailingly used to improve thecapacity and the flexibility of wireless mesh networks(WMNs). The System over heads that are generated by uncontrolled interface switching adversely decrease the performance of WMNs. To find a reasonable tradeoff between flexibility and switching overheads, we propose ahybrid channelassignment protocol (HCAP) for multiinterface WMNs. The HCAP adopts a static interfaceassignment strategy for nodes that have the heaviest loads to avoid frequent interface switching, whereas it adopts a hybrid interfaceassignment strategy for other nodes to improve the ability of adapting to flow change. In our implementation, we present a slotbased coordination policy. Extensive NS2 simulations demonstrate that the HCAP improves network capacity, enhances flexibility, and guarantees interflow fairness. KEYWORDS: Channel assignment, coordination, interface switching, multiple interfaces, wireless mesh network (WMN). I. INTRODUCTION In deployment of wireless mesh networks (WMNs) has quickly increased recently due to their significant advantages over other wireless networks. A typical WMN application consists of three levels: wired networks, the WMN backbone, and mesh clients. Wired networks contain most resources in WMNs, such as file servers, file transfer protocol servers, etc. The WMN backbone is a collection of static wireless mesh routers. Traffic loads between the wired network and mobile users in mesh clients are transmitted by the WMN backbone in a multihop manner. Mesh clients can connect to the WMN backbone by establishing either wired or wireless links with mesh routers. Most wireless networks, such as wireless local area networks, wireless metropolitan area net-works, wireless wide area networks, wireless sensor networks, wireless personal area networks, and cellular networks, can act as mesh clients. One example of WMN architecture is shown in We propose a novel channelassignment protocol for multi-interface WMNs. The proposed protocol does not need prior knowledge of loads. Nevertheless, it can automatically adapt to load change

Joint Congestion Control and Scheduling in Wireless Networks with Network Coding

published_or_final_versio

Optimization-Based Channel Constrained Data Aggregation Routing Algorithms in Multi-Radio Wireless Sensor Networks

In wireless sensor networks, data aggregation routing could reduce the number of data transmissions so as to achieve energy efficient transmission. However, data aggregation introduces data retransmission that is caused by co-channel interference from neighboring sensor nodes. This kind of co-channel interference could result in extra energy consumption and significant latency from retransmission. This will jeopardize the benefits of data aggregation. One possible solution to circumvent data retransmission caused by co-channel interference is to assign different channels to every sensor node that is within each other's interference range on the data aggregation tree. By associating each radio with a different channel, a sensor node could receive data from all the children nodes on the data aggregation tree simultaneously. This could reduce the latency from the data source nodes back to the sink so as to meet the user's delay QoS. Since the number of radios on each sensor node and the number of non-overlapping channels are all limited resources in wireless sensor networks, a challenging question here is to minimize the total transmission cost under limited number of non-overlapping channels in multi-radio wireless sensor networks. This channel constrained data aggregation routing problem in multi-radio wireless sensor networks is an NP-hard problem. I first model this problem as a mixed integer and linear programming problem where the objective is to minimize the total transmission subject to the data aggregation routing, channel and radio resources constraints. The solution approach is based on the Lagrangean relaxation technique to relax some constraints into the objective function and then to derive a set of independent subproblems. By optimally solving these subproblems, it can not only calculate the lower bound of the original primal problem but also provide useful information to get the primal feasible solutions. By incorporating these Lagrangean multipliers as the link arc weight, the optimization-based heuristics are proposed to get energy-efficient data aggregation tree with better resource (channel and radio) utilization. From the computational experiments, the proposed optimization-based approach is superior to existing heuristics under all tested cases

Distributed execution of cognitive relaying with time incentive: multiple PU scenario

The prime focus of this study is in developing distributed algorithms for cognitive relaying with time incentive for multiple primary users (CRTI-M). CRTI-M is a symbiotic paradigm in which the incumbent primary users (PUs) of the spectrum, with weak transmission links, seek cooperation from the cognitive secondary user (SU) nodes in their vicinity, and in return reward them with an incentive time for the latter's own communication. When relaying through the SU network, each PU can either use its own spectrum or that of the other PUs. Cross-layer optimization problems are formulated to enable both these possibilities in a multi-hop multi-channel cognitive radio network with the objective of maximizing the cumulative time incentive for the SUs. Corresponding distributed algorithms are developed, which face the challenge of meeting the constraints of the formulated problems with only local information and the lack of a centralized controller. Further, to make the CRTI-M schemes practically realizable, a MAC scheduling protocol is suggested, which gives emphasis to the distributed implementation and provides a unified framework for the PUs and SUs. Simulation results are furnished to demonstrate the effectiveness of the proposed algorithms

Providing protection in multi-hop wireless networks

We consider the problem of providing protection against failures in wireless networks subject to interference constraints. Typically, protection in wired networks is provided through the provisioning of backup paths. This approach has not been previously considered in the wireless setting due to the prohibitive cost of backup capacity. However, we show that in the presence of interference, protection can often be provided with no loss in throughput. This is due to the fact that after a failure, links that previously interfered with the failed link can be activated, thus leading to a “recapturing” of some of the lost capacity. We provide both an ILP formulation for the optimal solution, as well as algorithms that perform close to optimal. More importantly, we show that providing protection in a wireless network uses as much as 72% less protection resources as compared to similar protection schemes designed for wired networks, and that in many cases, no additional resources for protection are needed.National Science Foundation (U.S.) (Grant CNS-1116209)National Science Foundation (U.S.) (Grant CNS-0830961)United States. Defense Threat Reduction Agency (Grant HDTRA-09-1-005)United States. Air Force (Contract FA8721-05-C-0002

EMPoWER Hybrid Networks: Exploiting Multiple Paths over Wireless and ElectRical Mediums

Several technologies, such as WiFi, Ethernet and power-line communications (PLC), can be used to build residential and enterprise networks. These technologies often co-exist; most networks use WiFi, and buildings are readily equipped with electrical wires that can offer a capacity up to 1 Gbps with PLC. Yet, current networks do not exploit this rich diversity and often operate far below the available capacity. We design, implement, and evaluate EMPoWER, a system that exploits simultaneously several potentially-interfering mediums. It operates at layer 2.5, between the MAC and IP layers, and combines routing (to find multiple concurrent routes) and congestion control (to efficiently balance traffic across the routes). To optimize resource utilization and robustness, both components exploit the heterogeneous nature of the network. They are fair and efficient, and they operate only within the local area network, without affecting remote Internet hosts. We demonstrate the performance gains of EMPoWER, by simulations and experiments on a 22-node testbed. We show that PLC/WiFi, benefiting from the diversity offered by wireless and electrical mediums, provides significant throughput gains (up to 10x) and improves coverage, compared to multi-channel WiFi

A Distributed Joint Channel-Assignment, Scheduling and Routing Algorithm for Multi-Channel Ad Hoc Wireless Networks

Abstract — The capacity of ad hoc wireless networks can be substantially increased by equipping each network node with multiple radio interfaces that can operate on multiple non-overlapping channels. However, new scheduling, channelassignment, and routing algorithms are required to fully utilize the increased bandwidth in multi-channel multi-radio ad hoc networks. In this paper, we develop a fully distributed algorithm that jointly solves the channel-assignment, scheduling and routing problem. Our algorithm is an online algorithm, i.e., it does not require prior information on the offered load to the network, and can adapt automatically to the changes in the network topology and offered load. We show that our algorithm is provably efficient. That is, even compared with the optimal centralized and offline algorithm, our proposed distributed algorithm can achieve a provable fraction of the maximum system capacity. Further, the achievable fraction that we can guarantee is larger than that of some other comparable algorithms in the literature. I

A Socio-inspired CALM Approach to Channel Assignment Performance Prediction and WMN Capacity Estimation

A significant amount of research literature is dedicated to interference mitigation in Wireless Mesh Networks (WMNs), with a special emphasis on designing channel allocation (CA) schemes which alleviate the impact of interference on WMN performance. But having countless CA schemes at one's disposal makes the task of choosing a suitable CA for a given WMN extremely tedious and time consuming. In this work, we propose a new interference estimation and CA performance prediction algorithm called CALM, which is inspired by social theory. We borrow the sociological idea of a "sui generis" social reality, and apply it to WMNs with significant success. To achieve this, we devise a novel Sociological Idea Borrowing Mechanism that facilitates easy operationalization of sociological concepts in other domains. Further, we formulate a heuristic Mixed Integer Programming (MIP) model called NETCAP which makes use of link quality estimates generated by CALM to offer a reliable framework for network capacity prediction. We demonstrate the efficacy of CALM by evaluating its theoretical estimates against experimental data obtained through exhaustive simulations on ns-3 802.11g environment, for a comprehensive CA test-set of forty CA schemes. We compare CALM with three existing interference estimation metrics, and demonstrate that it is consistently more reliable. CALM boasts of accuracy of over 90% in performance testing, and in stress testing too it achieves an accuracy of 88%, while the accuracy of other metrics drops to under 75%. It reduces errors in CA performance prediction by as much as 75% when compared to other metrics. Finally, we validate the expected network capacity estimates generated by NETCAP, and show that they are quite accurate, deviating by as low as 6.4% on an average when compared to experimentally recorded results in performance testing