Cross layer routing and scheduling for multi-channel Wimax mesh networks

Broadband wireless networks are becoming increasingly popular due to their fast and inexpensive deployment and their capabilities of providing flexible and ubiquitous Internet access. Due to the limitation of shared resources in wireless mesh network such as bandwidth, spatial reuse is introduced for concurrent transmissions. The simultaneous transmissions face many challenges regarding interference on the ongoing transmission. To maximize the network performance of mesh networks in terms of spatial reuse, it is essential to consider a cross-layer for resource allocation in different layers such as the routing network layer, the scheduling resource allocation Media Access Control (MAC) layer and physical layer. Therefore, this thesis focuses on improving the spatial reuse for resource allocation mechanism including routing tree construction by taking into consideration the reliable path, channel assignment and scheduling algorithms. Firstly, a Fuzzy based Constructed Routing Tree (FLCRT) is proposed to incorporate fuzzy logic with routing to enable cognitive capability in packet forwarding for uplink or downlink communication. Secondly, the link-aware routing path is proposed to satisfy the connection lifetime and better routing stability for successful requirements of transmission using multi sponsor node technique. Then, a better understanding of reliability analysis is pursued in the context of homogeneous wireless network. Ultimately, heuristic resource allocation including channel assignment and centralized scheduling algorithms are proposed based on the cellular learning automata to enhance the number of concurrent transmissions in the network by efficiently reusing the spectrum spatially. The attempt of heuristic resource allocation algorithms is to find the maximal number of nodes that could transmit data concurrently. The numerical and simulation results show that FLCRT, Learning Automata Heuristic Channel Assignment (LAHCA), and Learning Automata Heuristic Centralized Scheduling (LAHCS) perform better in terms of scheduling length, channel utilization ratio, and average transmission delay as compared with the existing approaches. The proposed FLCRT scheme with respect to the number of subscriber station (SS) nodes performs better in decreasing the scheduling length, average transmission delay, and channel utilization ratio by 38%, 19%, and 38% compared with Interference-Load-Aware routing. LAHCA algorithm improves the number of channels in comparison with random selection algorithm by 8%. LAHCS algorithm using multi channels proposed by LAHCA can reduce the scheduling time, average transmission delay as well as enhance channel utilization ratio versus number of SS nodes by 7%, 8%, and 6% respectively compared with Nearest algorithm in higher traffic demands

Optimized query routing trees for wireless sensor networks

In order to process continuous queries over Wireless Sensor Networks (WSNs), sensors are typically organized in a Query Routing Tree (denoted as T) that provides each sensor with a path over which query results can be transmitted to the querying node. We found that current methods deployed in predominant data acquisition systems construct T in a sub-optimal manner which leads to significant waste of energy. In particular, since T is constructed in an ad hoc manner there is no guarantee that a given query workload will be distributed equally among all sensors. That leads to data collisions which represent a major source of energy waste. Additionally, current methods only provide a topological-based method, rather than a query-based method, to define the interval during which a sensing device should enable its transceiver in order to collect the query results from its children. We found that this imposes an order of magnitude increase in energy consumption. In this paper we present MicroPulse+, a novel framework for minimizing the consumption of energy during data acquisition in WSNs. MicroPulse+ continuously optimizes the operation of T by eliminating data transmission and data reception inefficiencies using a collection of in-network algorithms. In particular, MicroPulse+ introduces: (i) the Workload-Aware Routing Tree (WART) algorithm, which is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the critical path method; and (ii) the Energy-driven Tree Construction (ETC) algorithm, which balances the workload among nodes and minimizes data collisions. We show through micro-benchmarks on the CC2420 radio chip and trace-driven experimentation with real datasets from Intel Research and UC-Berkeley that MicroPulse+ provides significant energy reductions under a variety of conditions thus prolonging the longevity of a wireless sensor network

Impacts of Channel Switching Overhead on the Performance of Multicast in Wireless Mesh Networks

Wireless mesh networks (WMNs) have emerged as a promising technology for next generation wireless networking. A WMN extends network coverage using wireless mesh routers that communicate with each other via multi-hop wireless communications. One technique to increase the network capacity of WMNs is to use routers equipped with multiple radios capable of transmitting and receiving on multiple channels. In a Multi-Channel Multi-Radio wireless mesh network (MCMR WMN), nodes are capable of transmitting and receiving data simultaneously through different radios and at least theoretically doubling the average throughput. On the other hand, the use of multi-radio and multi-channel technology in many cases requires routers to switch channels for each transmission and/or reception. Channel switching incurs additional costs and delay. In this thesis, we present a simulation-based study of the impacts of channel switching overheads on the performance of multicast in MCMR WMNs. We study how channel switching overheads affect the performance metrics such as packet delivery ratio, throughput, end-to-end delay, and delay jitter of a multicast session. In particular, we examine: 1. the performance of multicast in MCMR WMNs with three orthogonal channels versus eleven overlapping channels defined in IEEE 802.11b. 2. the performance of the Minimum-interference Multi-channel Multi-radio Multicast (M4) algorithm with and without channel switching. 3. the performance of the Multi-Channel Minimum Number of Transmissions (MCMNT) algorithm (which does not do channel switching) in comparison with the M4 algorithm (which performs channel switching)

Data Collection and Capacity Analysis in Large-scale Wireless Sensor Networks

In this dissertation, we study data collection and its achievable network capacity in Wireless Sensor Networks (WSNs). Firstly, we investigate the data collection issue in dual-radio multi-channel WSNs under the protocol interference model. We propose a multi-path scheduling algorithm for snapshot data collection, which has a tighter capacity bound than the existing best result, and a novel continuous data collection algorithm with comprehensive capacity analysis. Secondly, considering most existing works for the capacity issue are based on the ideal deterministic network model, we study the data collection problem for practical probabilistic WSNs. We design a cell-based path scheduling algorithm and a zone-based pipeline scheduling algorithm for snapshot and continuous data collection in probabilistic WSNs, respectively. By analysis, we show that the proposed algorithms have competitive capacity performance compared with existing works. Thirdly, most of the existing works studying the data collection capacity issue are for centralized synchronous WSNs. However, wireless networks are more likely to be distributed asynchronous systems. Therefore, we investigate the achievable data collection capacity of realistic distributed asynchronous WSNs and propose a data collection algorithm with fairness consideration. Theoretical analysis of the proposed algorithm shows that its achievable network capacity is order-optimal as centralized and synchronized algorithms do and independent of network size. Finally, for completeness, we study the data aggregation issue for realistic probabilistic WSNs. We propose order-optimal scheduling algorithms for snapshot and continuous data aggregation under the physical interference model

OLSR-Aware cross-layer channel access scheduling in wireless mesh networks

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Master's) -- Bilkent University, 2009.Includes bibliographical references leaves 63-68.A wireless mesh network (WMN) is a communications network in which the nodes are organized to form a mesh topology. WMNs are expected to resolve the limitations and significantly improve the performance of wireless ad-hoc, local area, personal area, and metropolitan area networks, which is the reason that they are experiencing fast-breaking progress and deployments. WMNs typically employ spatial TDMA (STDMA) based channel access schemes which are suitable for the high traffic demands of WMNs. Current research trends focus on using loosening the strict layered network implementation in order to look for possible ways of performance improvements. In this thesis, we propose two STDMA-based cross-layer OLSR-Aware channel access scheduling schemes (one distributed, one centralized) that aim better utilizing the network capacity and increasing the overall application throughput by using OLSR-specific routing layer information in link layer scheduling. The proposed centralized algorithm provides a modification of the traditional vertex coloring algorithm while the distributed algorithm is a fully distributed pseudo-random algorithm in which each node makes decisions using local information. Proposed schemes are compared against one another and against their Non-OLSR-Aware versions via extensive ns-2 simulations. Our simulation results indicate that MAC layer can obtain OLSR-specific information with no extra control overhead and utilizing OLSR-specific information significantly improves the overall network performance both in distributed and centralized schemes. We further show that link layer algorithms that target the maximization of concurrent slot allocations do not necessarily increase the application throughput.Kaş, MirayM.S

Interference Modeling And Control In Wireless Networks

With the successful commercialization of IEEE802.11 standard, wireless networks have become a tight-knit of our daily life. As wireless networks are increasingly applied to real- time and mission-critical tasks, how to ensuring real-time, reliable data delivery emerges as an important problem. However, wireless communication is subject to various dynamics and uncertainties due to the broadcast nature of wireless signal. In particular, co-channel interfer- ence not only reduces the reliability and throughput of wireless networks, it also increases the variability and uncertainty in data communication [64, 80, 77]. A basis of interference control is the interference model which \emph{predicts} whether a set of concurrent transmissions may interfere with one another. Two commonly used models, the \textit{SINR model} and the \textit{radio-K model}, are thoroughly studied in our work. To address the limitations of those models, we propose the physical-ratio-K(PRK) interference model as a reliablility-oriented instantiation of the ratio-K model, where the link-specific choice of K adapts to network and environmental conditions as well as application QoS requirements to ensure certain minimum reliability of every link. On the other hand, the interference among the transmissions, limits the number of con- current transmissions. We formulate the concept of \emph{interference budget} that, given a set of scheduled transmissions in a time slot, characterizes the additional interference power that can be tolerated by all the receivers without violating the application requirement on link reliability. We propose the scheduling algorithm \emph{iOrder} that optimizes link ordering by considering both interference budget and queue length in scheduling. Through both simulation and real-world experiments, we observe that optimizing link ordering can improve the performance of existing algorithms by a significant. Based on the strong preliminary research result on interference modeling and control, we will extend our method into distributed protocol designs. One future work will focus on imple- menting the \textit{PRK model} in a distributed protocols. We will also explore the benefits of using multiple channels in the interference control

Data Aggregation Scheduling in Wireless Networks

Data aggregation is one of the most essential data gathering operations in wireless networks. It is an efficient strategy to alleviate energy consumption and reduce medium access contention. In this dissertation, the data aggregation scheduling problem in different wireless networks is investigated. Since Wireless Sensor Networks (WSNs) are one of the most important types of wireless networks and data aggregation plays a vital role in WSNs, the minimum latency data aggregation scheduling problem for multi-regional queries in WSNs is first studied. A scheduling algorithm is proposed with comprehensive theoretical and simulation analysis regarding time efficiency. Second, with the increasing popularity of Cognitive Radio Networks (CRNs), data aggregation scheduling in CRNs is studied. Considering the precious spectrum opportunity in CRNs, a routing hierarchy, which allows a secondary user to seek a transmission opportunity among a group of receivers, is introduced. Several scheduling algorithms are proposed for both the Unit Disk Graph (UDG) interference model and the Physical Interference Model (PhIM), followed by performance evaluation through simulations. Third, the data aggregation scheduling problem in wireless networks with cognitive radio capability is investigated. Under the defined network model, besides a default working spectrum, users can access extra available spectrum through a cognitive radio. The problem is formalized as an Integer Linear Programming (ILP) problem and solved through an optimization method in the beginning. The simulation results show that the ILP based method has a good performance. However, it is difficult to evaluate the solution theoretically. A heuristic scheduling algorithm with guaranteed latency bound is presented in our further investigation. Finally, we investigate how to make use of cognitive radio capability to accelerate data aggregation in probabilistic wireless networks with lossy links. A two-phase scheduling algorithm is proposed, and the effectiveness of the algorithm is verified through both theoretical analysis and numerical simulations

Power-source-aware adaptive routing in wireless sensor networks

Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013.Thesis (Ph. D.) -- Bilkent University, 2013.Includes bibliographical references leaves 112-122.A wireless sensor network (WSN) is a collection of sensor nodes distributed over an area of interest to accomplish a certain task by monitoring environmental and physical conditions and sending the collected data to a special node called sink. Most studies on WSNs consider nodes to be powered with irreplaceable batteries, which limits network lifetime. There are, however, perpetual power source alternatives as well, including mains electricity and energy harvesting mechanisms, which can be utilized by at least some portion of the sensor nodes to further prolong the network lifetime. Our aim here is to increase the lifetime of such WSNs with heterogeneous power sources by centralized or distributed routing algorithms that distinguish battery- and mains-powered nodes in routing, so that energy consuming tasks are carried out mostly by mains-powered nodes. We first propose a framework for a class of routing algorithms, which forms and uses a backbone topology consisting of all mains-powered nodes, including the sinks, and possibly some battery-powered nodes, to route data packets. We propose and evaluate a set of centralized algorithms based on this framework, and our simulation results show that our algorithms can increase network lifetime by up to more than a factor of two. We also propose a fully distributed power-source-aware backbone-based routing algorithm (PSABR) that favors mains-powered nodes as relay nodes. We validate and evaluate our distributed algorithm with extensive ns-2 simulations and our results show that the proposed distributed algorithm can enhance network lifetime significantly with a low control messaging overhead. Besides wireless technology independent routing solutions, we also propose a technology specific power-source-aware routing solution (PSAR) for sensor and ad hoc networks which use 802.15.4/ZigBee as the wireless technology. Our solution is fully distributed, tree-based, and traffic-adaptive. It utilizes some protocol specific properties of ZigBee, such as distributed and hierarchical address assignment, to eliminate battery-powered nodes on the routing paths as much as possible. To validate and evaluate our ZigBee-specific algorithm, we first implemented ZigBee extensions to ns-2 simulator and then implemented and simulated our protocol in this extended ns-2 environment. Our results show that the proposed algorithm operates efficiently and can increase network lifetime without increasing the path lengths significantly, compared to the default ZigBee routing algorithm.Tekkalmaz, MetinPh.D