Abdusy Syarif

Evolutionary multi-objective based approach for wireless sensor network deployment

This paper is a study about deployment strategy for achieving coverage and connectivity as two fundamental issues in wireless sensor networks. To achieve the best deployment, a new approach based on elitist non-dominated sorting genetic algorithm (NSGA-II) is used. There are two objectives in this study, connectivity and coverage. We defined a fitness function to achieve the best nodes deployment. Further we performed simulation to verify and validate the deployment of wireless sensor network as an output from the proposed mechanism. Some performance parameters have been measured to investigate and analyze the proposed sensor-deployment. The simulation results show that the proposed algorithm can maintain the coverage and connectivity in a given sensing area with a relatively small number of sensor nodes.

Performance evaluation AODV routing protocol on ad hoc hybrid network testbed using PDAs

This paper presents our work on the test bed implementation of hybrid ad hoc network. In mobile ad hoc network (MANET), nodes are equipped with wireless device which provides self-managing and self-organizing capability, even when there is no network infrastructure present. Ad hoc hybrid network which enables mobile nodes to form instant communication without depending on infrastructure network can communicate with the other devices through LAN or Internet. The function of ad hoc network is very much dependent on the routing protocol that determines the path between nodes in network. ad hoc on-demand distance vector (AODV) is a kind of a reactive routing protocol for ad hoc network. This protocol is the most popular and widely used routing protocol in research and deployment. In this work, we review and implement AODV routing protocol in a testbed consisting of some PCs, laptops (using Linux Red Hat 9.0 and Fedora Core 2), and PDAs Hewlett Packard iPAQ 5550 series (using Linux Familiar v0.7.2 with Opie 1.2). We particularly focus on the AODV-UU routing protocol. We provide packages (by cross compiling) AODV for PocketPC (PDA), and evaluate the packet delivery ratio, end-to-end delay, and routing overhead of different ad-hoc hybrid network topologies. The testbed implementation result for the average packet delivery ratio is 99.57%, and the end-to-end delay is 1.004 s and the routing overhead is 1,360.36 bps.

Performance analysis of evolutionary multi-objective based approach for deployment of wireless sensor network with the presence of fixed obstacles

In this paper, a study about wireless sensor network (WSN) deployment strategy is demonstrated and made workable for the use of multi-objective approach. The development of sensor nodes by considering multiple objectives and existence of fixed obstacles is an important optimization problem. There are two objectives in this study, connectivity and coverage as two fundamental issues in wireless sensor networks deployment. In this work a multi-objective evolutionary algorithms based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to address this problem. Two proposed functions, ranking function and fitness function, are used to determine the best optimal solution from Pareto optimal fronts. Further we presented simulation and analysis to verify and validate the deployment of wireless sensor network in area with the presence of permanent obstacles.

Performance comparison of modified AODV in reference point group mobility and random waypoint mobility models

A Mobile Adhoc Network (MANET) is characterized by high mobility, non-infrastructure network, and dynamic topology. This nature make MANET have some constraints such as energy constraints, limited bandwidth, and less memory. Energy consumption becomes an important issue in manet to cover the sustainability of the communication process. We have proposed optimize routing protocol based on AODV routing protocol for hybrid network. We used reverse mechanism to optimize the AODV routing protocol. In this paper, we will analyze the performance of our proposed protocol in term of energy consumption, packet delivery ratio, end to end delay and routing overhead. We evaluate our proposed protocol with NS-2, with some scenario using random waypoint and reference point group mobility model. In the Random Waypoint model (RWP), each node chooses a new destination randomly and then moves towards the destination at a constant speed. In RPGM, it will create some group of nodes. Each group has a logical center that defines the entire groups motion behavior, including location, speed, direction, and acceleration. The simulation result shows that our modified protocol is outperform in random waypoint rather than in rpgm. In term of energy consumption, our protocol achieved lower consumption for random waypoint mobility compare to the reference point group mobility model.

Adding gateway mode for R-AODV routing protocol in hybrid ad hoc network

In mobile ad hoc networks (MANET), routing protocol plays the most important role. For more than one decade, Ad hoc On-demand Distance Vector (AODV) routing protocol becomes attention and research focus on MANET widely. A lot of protocols proposed to improve and optimize AODV performance. Yet, many of those do not consider the needs of node accessing Internet via infrastructure network. In this paper, we proposed a new variant of routing protocol AODV by combining two protocols, R-AODV [9] and AODV+ [10], we called it R-AODV+, so it will be able to be implemented in hybrid ad hoc networks. The reason of proposed R-AODV+ protocol to be achieved is the best performance and reliable. Nodes that attain a connection to the Internet will be able to have access with a gateway node support. In this work, we performed a simulation using NS-2 and measured the performance of the proposed protocol by measuring the routing overhead, end-to-end delay and packet delivery ratio. The result of the simulation shows that our proposed protocol outperformed AODV+.

New Path Centrality Based on Operator Calculus Approach for Wireless Sensor Network Deployment

One of the greatest challenges in computing and estimating the important node metrics of a structural graph is centrality. Since centrality is an essential concept in social network analysis (SNA), it is used to define the importance of a node in a network like a wireless sensor network (WSN). Route optimization is another important feature in a wireless sensor network. This paper proposes an alternative solution to route optimization problems by using the multi-constrained optimal path (MCOP) approach. A new metric called path operator calculus (POC) is proposed as an alternative way to determine nodes with high centrality in wireless sensor network deployment. The estimation of this new metric is based on network topology by using the operator calculus approach, which produces the feasible paths for each node to the sink node. In order to define the path centrality of the network, the proposed approach takes into account two constraints for each node: energy and bit error rate (BER). The experimental evaluation shows improved performance in terms of delivery ratio, latency, throughput, delay, energy remaining and routing overhead.

Operator calculus approach for route optimizing and enhancing wireless sensor network

Abstract Route optimization is one of important feature in wireless sensor networks in order to enhancing the life time of WSNs. Since Centrality is one of the greatest challenges in computing and estimating the important node metrics of a structural graph, it is necessary to calculate and determine the importance of a node in a network. This paper proposes an alternative way to optimizing the route problems which is based on multi-constrained optimal path (MCOP) and operator calculus approach. A novel routing protocol called Path Operator Calculus Centrality (POCC) is proposed as a new method to determine the main path which contains high centrality nodes in a wireless sensor network deployment. The estimation of centrality is using the operator calculus approach based on network topology which provides optimal paths for each source node to base station. Some constraints such as energy level and bit error rate (BER) of node are considered to define the path centrality in this approach. The simulation evaluation shows improved performance in terms of energy consumption and network lifetime.

Search based software engineering on evolutionary multi-objective approach

The works on Search Based Software Engineering (SBSE) have been a big increase in the last decade. An approach to software engineering in which search based optimisation algorithms are applied to address problems in software engineering. SBSE has been applied to problems throughout the software engineering lifecycle, from requirements and project planning to maintenance and re-engineering. This paper provides a modification and an implementation of SBSE on evolutionary multi-objective based approach for deployment of wireless sensor network (WSN) with the presence of fixed obstacle. In this work a multi-objective evolutionary algorithms based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to address the deployment problem. Two functions namely ranking function and fitness function are used to select the best optimal solution from Pareto optimal fronts.

A combined path selection and admission control scheme for IPTV in IEEE 802.16j MMR networks

This paper proposes a new mechanism of path selection and admission control for IPTV in IEEE 802.16j simultaneously. The proposed mechanism takes into account some constraints of Quality of Services (QoS) which are required by real-time applications, such as available bandwidth, end-to-end delay, number of hops between MR-BS and SS as well as quality of radio signal. With all these four constraints, selecting the best path becomes a multi-objective optimization problem, since we have two criteria to maximize and two other criteria to minimize. It makes selection process of the optimal path more difficult to find a solution in polynomial time. To solve this multi-constrained problem, the proposed approach applied a cost function which simplifies the multi-objective problem into single objective. This function provides a deterministic solution which takes into account all the above constraints. To evaluate the proposed mechanism, we study the performance of the proposed approach through various simulation scenarios. The results show that the proposed mechanism outperforms other studies.