The New Multipoint Relays Selection in OLSR using Particle Swarm Optimization

The standard optimized link state routing (OLSR) introduces an interesting concept, the multipoint relays (MPRs), to mitigate message overhead during the flooding process. This paper propose a new algorithm for MPRs selection to enhance the performance of OLSR using particle swarm optimization sigmoid increasing inertia weight (PSOSIIW). The sigmoid increasing inertia weight has significance improve the particle swarm optimization (PSO) in terms of simplicity and quick convergence towards optimum solution. The new fitness function of PSOSIIW, packet delay of each node and degree of willingness are introduced to support MPRs selection in OLSR. The throughput, packet loss and end-to-end delay of the proposed method are examined using network simulator 2 (ns2).  Overall results indicate that OLSR-PSOSIIW has shown good performance compared to the standard OLSR and OLSR-PSO, particularly for the throughput and end-to-end delay. Generally the proposed OLSR-PSOSIIW shows advantage of using PSO for optimizing routing paths in the MPRs selection algorithm

MPR selection to the OLSR quality of service in MANET using minmax algorithm

Optimized link state routing (OLSR) is a routing protocol that has a small delay, low traffic control, support the application of denser networks, and adopts the concept of multipoint relays (MPR). The problem of OLSR is routing table updating which continually causes excessive packet delivery, and energy consumption becomes increased. This article proposes the improvement of OLSR performance using the min-max algorithm based on the quality of service (QoS) with considering the density of the node. The Min-max algorithm works in selecting MPR nodes based on the largest signal range. The QoS parameters analyzed with a different number of nodes are packet delivery ratio (PDR), throughput, delay, energy consumption, and topology control (TC). Simulation result of network simulator version 2 (NS-2) shows that OLSR performance using the min-max algorithm can increase PDR of 91.17%, packet loss of 60.77% and reduce topology control packet of 8.07%, energy consumption of 16.82% compared with standard OLSR

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

An analysis of the lifetime of OLSR networks

The Optimized Link State Routing (OLSR) protocol is a well-known route discovery protocol for ad-hoc networks. OLSR optimizes the flooding of link state information through the network using multipoint relays (MPRs). Only nodes selected as MPRs are responsible for forwarding control traffic. Many research papers aim to optimize the selection of MPRs with a specific purpose in mind: e.g., to minimize their number, to keep paths with high Quality of Service or to maximize the network lifetime (the time until the first node runs out of energy). In such analyzes often the effects of the network structure on the MPR selection are not taken into account. In this paper we show that the structure of the network can have a large impact on the MPR selection. In highly regular structures (such as grids) there is even no variation in the MPR sets that result from various MPR selection mechanisms. Furthermore, we study the influence of the network structure on the network lifetime problem in a setting where at regular intervals messages are broadcasted using MPRs. We introduce the ’maximum forcedness ratio’, as a key parameter of the network to describe how much variation there is in the lifetime results of various MPR selection heuristics. Although we focus our attention to OLSR, being a widely implemented protocol, on a more abstract level our results describe the structure of connected sets dominating the 2-hop neighborhood of a node

Automatic Optimisation of Reliable Collaborative Services in OLSR Mobile Ad Hoc Networks

International audienceFuture Network based Operations (NbO) will strongly rely on Mobile Ad hoc Networks (MANET), due to urban area, tactical mobility and assymetric operation management. These networks will support multiple collaborative services, such as sensor to shooters, reachback, maintenance of Common Operational Picture (COP). Both networks and services will have to be managed with no or limited operator intervention, still providing reliable behavior in spite of aggressive environments. At routing level, we present how to preserve 2-connectivity by adapting the Optimised Link State Routing Protocol (OLSR). We also introduce the concept of active subnet management to retrieve maximal operational gain from collaborative services. Following a constraint solving method, the paper shows how to maximise the subnet of actors, while satisfying 2-connectivity, reactivity and communication quality constraints. We demonstrate the approach on simulating real world NbO

Analisis Kinerja Protocol OLSR Pada Jaringan Ad Hoc

Abstrak: Analisis kinerja dengan menggunakan protocol Optimized Link State Routing (OLSR) pada jaringan ad hoc telah didapatkan hasil Quality of Service atau QoS terhadap nilai throughput, packet loss dan delay serta uji performa proses transfer data dilakukan dengan menggunakan software Network Simulator 3 (NS-3) pada sistem operasi Linux Ubuntu, berdasarkan jumlah node yang terus ditambah sesuai dengan skenario pengujian pada jaringan ad hoc. Skenario pengujian dilakukan dengan penambahan node secara bertahap mulai dari 10 node, kemudian ditambahkan menjadi 20 node, sampai berjumlah 40 node. Hasil analisis kinerja protocol Optimized Link State Routing (OLSR) serta pengukuran yang didapatkan terhadap nilai throughput, menghasilkan nilai rata-rata sebesar 3.1872 Kbps sehingga termasuk ke dalam kategori bagus. Nilai packet loss menghasilkan rata-rata sebesar 3,48% termasuk kedalam kategori bagus dan nilai delay menghasilkan rata-rata 6.824 ms yang juga masuk ke dalam kategori bagus. Hasil akhir analisis kinerja dengan menggunakan protocol Optimized Link State Routing (OLSR) pada jaringan ad hoc telah disajikan dalam bentuk grafik untuk memudahkan proses pengamatan dan penelitian selanjutnya