A Multiobjective Optimization Framework for Routing in Wireless Ad Hoc Networks

Wireless ad hoc networks are seldom characterized by one single performance metric, yet the current literature lacks a flexible framework to assist in characterizing the design tradeoffs in such networks. The aim of this paper is not to propose another routing strategy. Instead, we address this problem by proposing a new modeling framework for routing in ad hoc networks, which will result in a better understanding of network behavior and performance when multiple criteria are relevant. Our approach is to take a holistic view of the network that captures the cross-interactions among interference management techniques implemented at various layers of the protocol stack. The resulting framework is a complex multiobjective optimization problem that can be solved through existing multiobjective search techniques. In this contribution, we present the Pareto optimal sets for an example sensor network when delay, robustness and energy are considered

Multi-Objective Cross-Layer Optimization for Selection of Cooperative Path Pairs in Multihop Wireless Ad hoc Networks

This paper focuses in the selection of an optimal path pair for cooperative diversity based on cross-layer optimization in multihop wireless ad hoc networks. Cross-layer performance indicators, including power consumption, signal-to-noise ratio, and load variance are optimized using multi-objective optimization (MOO) with Pareto method. Consequently, optimization can be performed simultaneously to obtain a compromise among three resources over all possible path pairs. The Pareto method is further compared to the scalarization method in achieving fairness to each resource. We examine the statistics of power consumption, SNR, and load variance for both methods through simulations. In addition, the complexity of the optimization of both methods is evaluated based on the required computing time

A Multiobjective Performance Evaluation Framework for Routing in Wireless Ad Hoc Networks

RoutingInternational audienceWireless ad hoc networks are seldom characterized by one single performance metric, yet the current literature lacks a flexible framework to assist in characterizing the design tradeoffs in such networks. The aim of this paper is not to propose another routing strategy. Instead, we address this problem by proposing a new modeling framework for routing in ad hoc networks, which will result in a better understanding of network behavior and performance when multiple criteria are relevant. Our approach is to take a holistic view of the network that captures the cross-interactions among interference management techniques implemented at various layers of the protocol stack. The resulting framework is a complex multiob- jective optimization problem that can be solved through existing multiobjective search techniques. In this contribution, we present the Pareto optimal sets for an example sensor network when delay, robustness and energy are considered

GSAR: Greedy Stand-Alone Position-Based Routing protocol to avoid hole problem occurance in Mobile Ad Hoc Networks

The routing process in a Mobile Ad Hoc Network (MANET) poses critical challenges because of its features such as frequent topology changes and resource limitations. Hence, designing a reliable and dynamic routing protocol that satisfies MANET requirements is highly demanded. The Greedy Forwarding Strategy (GFS) has been the most used strategy in position-based routing protocols. The GFS algorithm was designed as a high-performance protocol that adopts hop count in soliciting shortest path. However, the GFS does not consider MANET needs and is therefore insufficient in computing reliable routes. Hence, this study aims to improve the existing GFS by transforming it into a dynamic stand-alone routing protocol that responds swiftly to MANET needs, and provides reliable routes among the communicating nodes. To achieve the aim, two mechanisms were proposed as extensions to the current GFS, namely the Dynamic Beaconing Updates Mechanism (DBUM) and the Dynamic and Reactive Reliability Estimation with Selective Metrics Mechanism (DRESM). The DBUM algorithm is mainly responsible for providing a node with up-to-date status information about its neighbours. The DRESM algorithm is responsible for making forwarding decisions based on multiple routing metrics. Both mechanisms were integrated into the conventional GFS to form Greedy Stand-Alone Routing (GSAR) protocol. Evaluations of GSAR were performed using network simulator Ns2 based upon a defined set of performance metrics, scenarios and topologies. The results demonstrate that GSAR eliminates recovery mode mechanism in GFS and consequently improve overall network performance. Under various mobility conditions, GSAR avoids hole problem by about 87% and 79% over Greedy Perimeter Stateless Routing and Position-based Opportunistic Routing Protocol respectively. Therefore, the GSAR protocol is a reasonable alternative to position-based unicast routing protocol in MANET