A Review of the Energy Efficient and Secure Multicast Routing Protocols for Mobile Ad hoc Networks

This paper presents a thorough survey of recent work addressing energy efficient multicast routing protocols and secure multicast routing protocols in Mobile Ad hoc Networks (MANETs). There are so many issues and solutions which witness the need of energy management and security in ad hoc wireless networks. The objective of a multicast routing protocol for MANETs is to support the propagation of data from a sender to all the receivers of a multicast group while trying to use the available bandwidth efficiently in the presence of frequent topology changes. Multicasting can improve the efficiency of the wireless link when sending multiple copies of messages by exploiting the inherent broadcast property of wireless transmission. Secure multicast routing plays a significant role in MANETs. However, offering energy efficient and secure multicast routing is a difficult and challenging task. In recent years, various multicast routing protocols have been proposed for MANETs. These protocols have distinguishing features and use different mechanismsComment: 15 page

Cross-layer design for network performance optimization in wireless networks

In this dissertation, I use mathematical optimization approach to solve the complex network problems. Paper l and paper 2 first show that ignoring the bandwidth constraint can lead to infeasible routing solutions. A sufficient condition on link bandwidth is proposed that makes a routing solution feasible, and then a mathematical optimization model based on this sufficient condition is provided. Simulation results show that joint optimization models can provide more feasible routing solutions and provide significant improvement on throughput and lifetime. In paper 3 and paper 4, an interference model is proposed and a transmission scheduling scheme is presented to minimize the end-to-end delay. This scheduling scheme is designed based on integer linear programming and involves interference modeling. Using this schedule, there are no conflicting transmissions at any time. Through simulation, it shows that the proposed link scheduling scheme can significantly reduce end-to-end latency. Since to compute the maximum throughput is an NP-hard problem, efficient heuristics are presented in Paper 5 that use sufficient conditions instead of the computationally-expensive-to-get optimal condition to capture the mutual conflict relation in a collision domain. Both one-way transmission and two-way transmission are considered. Simulation results show that the proposed algorithms improve network throughput and reduce energy consumption, with significant improvement over previous work on both aspects. Paper 6 studies the complicated tradeoff relation among multiple factors that affect the sensor network lifetime and proposes an adaptive multi-hop clustering algorithm. It realizes the best tradeoff among multiple factors and outperforms others that do not. It is adaptive in the sense the clustering topology changes over time in order to have the maximum lifetime --Abstract, page iv

Networked Computing in Wireless Sensor Networks for Structural Health Monitoring

This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We establish that this problem is NP-hard. By relaxing the delay constraint, we derive a lower bound to this problem. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We further present a distributed version of the approximate algorithm. We present both simulation and experimentation results to demonstrate the effectiveness of these algorithms

Bandwidth and Energy Consumption Tradeoff for IEEE 802.15.4 in Multihop Topologies

IEEE 802.15.4, Multi-hop,ZigBee,WSNwe analyze IEEE 802.15.4 mechanisms including node organization, MAC mechanisms, energy conservation, topology construction and node association. We detail how we should modify IEEE 802.15.4 to cope efficiently with multihop topologies, scheduling the transmissions. We quantify the impact of the cluster-tree algorithm on the network performances. We expose how the overall throughput can be improved with a novel cluster-tree construction algorithm defined formally as a Mixed Integer Linear Programming formulation. We quantify the impact of each parameter on the performances of IEEE 802.15.4. In particular, we present a self-configuration algorithm to dynamically adjust the Backoff Exponent so that the protocol always operates in optimal conditions

Optimization and Learning in Energy Efficient Cognitive Radio System

Energy efficiency and spectrum efficiency are two biggest concerns for wireless communication. The constrained power supply is always a bottleneck to the modern mobility communication system. Meanwhile, spectrum resource is extremely limited but seriously underutilized. Cognitive radio (CR) as a promising approach could alleviate the spectrum underutilization and increase the quality of service. In contrast to traditional wireless communication systems, a distinguishing feature of cognitive radio systems is that the cognitive radios, which are typically equipped with powerful computation machinery, are capable of sensing the spectrum environment and making intelligent decisions. Moreover, the cognitive radio systems differ from traditional wireless systems that they can adapt their operating parameters, i.e. transmission power, channel, modulation according to the surrounding radio environment to explore the opportunity. In this dissertation, the study is focused on the optimization and learning of energy efficiency in the cognitive radio system, which can be considered to better utilize both the energy and spectrum resources. Firstly, drowsy transmission, which produces optimized idle period patterns and selects the best sleep mode for each idle period between two packet transmissions through joint power management and transmission power control/rate selection, is introduced to cognitive radio transmitter. Both the optimal solution by dynamic programming and flexible solution by reinforcement learning are provided. Secondly, when cognitive radio system is benefited from the theoretically infinite but unsteady harvested energy, an innovative and flexible control framework mainly based on model predictive control is designed. The solution to combat the problems, such as the inaccurate model and myopic control policy introduced by MPC, is given. Last, after study the optimization problem for point-to-point communication, multi-objective reinforcement learning is applied to the cognitive radio network, an adaptable routing algorithm is proposed and implemented. Epidemic propagation is studied to further understand the learning process in the cognitive radio network

Energy-efficient multi-criteria packet forwarding in multi-hop wireless networks

Reliable multi-hop packet forwarding is an important requirement for the implementation of realistic large-scale wireless ad-hoc networks. However, packet forwarding methods based on a single criterion, such as the traditional greedy geographic forwarding, are not sufficient in most realistic wireless settings because perfect-reception-within-rangecannot be assumed. Furthermore, methods where the selection of intermediate relaying nodes is performed at the transmitter-side do not adapt well to rapidly changing network environments. Although a few link-aware geographic forwarding schemes have been reported in the literature, the tradeoffs between multiple decision criteria and their impact on network metrics such as throughput, delay and energy consumption have not been studied. This dissertation presents a series of strategies aimed at addressing the challenges faced by the choice of relay nodes in error-prone dynamic wireless network environments. First, a single-criterion receiver-side relay election (RSRE) is introduced as a distributed alternative to the traditional transmitter-side relay selection. Contrary to the transmitter- side selection, at each hop, an optimal node is elected among receivers to relay packets toward the destination. Next, a multi-criteria RSRE, which factors multiple decision criteria in the election process at lower overhead cost, is proposed. A general cost metric in the form of a multi-parameter mapping function aggregates decision criteria into a single metric used to rank potential relay candidates. A two-criteria RSRE case study shows that a proper combination of greedy forwarding and link quality leads to higher energy efficiency and substantial improvement in the end-to-end delay. Last, mesh multi-path forwarding methods are examined. A generalized mesh construction algorithm in introduced to show impact of a mesh structure on network performance