Optimum Node Placement in Wireless Opportunistic Routing Networks

In recent years there has been a growing interest in opportunistic routing as a way to increase the capacity of wireless networks by exploiting its broadcast nature. In contrast to traditional uni-path routing, in opportunistic routing the nodes overhearing neighbor¿s transmissions can become candidates to forward the packets towards the destination. In this paper we address the question: What is the maximum performance that can be obtained using opportunistic routing? To answer this question we use an analytical model that allows to compute the optimal position of the nodes, such that the progress towards the destination is maximized. We use this model to compute bounds to the minimum expected number of transmissions that can be achieved in a network using opportunistic routing.This work was supported by the Spanish Ministerio de Ciencia e Innovacion through the Projects TIN2010-21378-C02-01 and TIN2010-21378-C02-02 and by the Generalitat de Catalunya through Project 2009-SGR-1167.Cerdá Alabern, L.; Darehshoorzadeh, A.; Pla, V. (2013). Optimum Node Placement in Wireless Opportunistic Routing Networks. Ad Hoc Networks. 11(8):2273-2287. https://doi.org/10.1016/j.adhoc.2013.05.010S2273228711

FRCA: A Novel Flexible Routing Computing Approach for Wireless Sensor Networks

In wireless sensor networks, routing protocols with immutable network policies lacking the flexibility are generally incapable of maintaining desired performance due to the complicated and changeable environment situations and application requirements. The proposed “Flexible Routing Computing Approach (FRCA)” is a novel distributed and probabilistic computing approach capable of modifying or upgrading routing policies on the fly with low cost, which effectively enhances the flexibility of routing protocols. FRCA models the routing metric as a forwarding probability distribution for routing decisions. This model depends on three elements, the physical quantities collected at sensor nodes, the built-in base math functions, and the routing parameters. These elements are all user-oriented and can be specified to implement multifarious complicated network policies meeting different performance requirements. More significantly, through distributing routing parameters from the sink to end nodes, operators are allowed to adjust network policies on the fly without the interruption of network services. Through extensive performance evaluation studies and simulations, the results demonstrated that routing protocols designed based on FRCA could achieve better performance compared to its state-of-the-art counterparts regarding network lifetime, energy consumption, and duplicate packets as well as ensure high flexibility during network policies modification or upgrade

Resource allocation for dataflow applications in FANETs using anypath routing

Management of network resources in advanced IoT applications is a challenging topic due to their distributed nature from the Edge to the Cloud, and the heavy demand of real-time data from many sources to take action in the deployment. FANETs (Flying Ad-hoc Networks) are a clear example of heterogeneous multi-modal use cases, which require strict quality in the network communications, as well as the coordination of the computing capabilities, in order to operate correctly the final service. In this paper, we present a Virtual Network Embedding (VNE) framework designed for the allocation of dataflow applications, composed of nano-services that produce or consume data, in a wireless infrastructure, such as an airborne network. To address the problem, an anypath-based heuristic algorithm that considers the quality demand of the communication between nano-services is proposed, coined as Quality-Revenue Paired Anypath Dataflow VNE (QRPAD-VNE). We also provide a simulation environment for the evaluation of its performance according to the virtual network (VN) request load in the system. Finally, we show the suitability of a multi-parameter framework in conjunction with anypath routing in order to have better performance results that guarantee minimum quality in the wireless communications.Xunta de Galicia | Ref. ED431C 2022/04 T254Ministerio de Universidades | Ref. FPU19/01284Agencia Estatal de Investigación | Ref. PCI2020-112174Agencia Estatal de Investigación | Ref. PID2020-113795RB-C33Agencia Estatal de Investigación | Ref. PID2020-116329GB-C21Universidade de Vigo/CISU

Fuzzy and Position Particle Swarm Optimized Routing in VANET

In Intelligent Transport Systems, traffic management and providing stable routing paths between vehicles using vehicular ad hoc networks (VANET\u27s) is critical. Lots of research and several routing techniques providing a long path lifetime have been presented to resolve this issue. However, the routing algorithms suffer excessive overhead or collisions when solving complex optimization problems. In order to improve the routing efficiency and performance in the existing schemes, a Position Particle Swarm Optimization based on Fuzzy Logic (PPSO-FL) method is presented for VANET that provides a high-quality path for communication between nodes. The PPSO-FL has two main steps. The first step is selecting candidate nodes through collectively coordinated metrics using the fuzzy logic technique, improving packet delivery fraction, and minimizing end-to-end delay. The second step is the construction of an optimized routing model. The optimized routing model establishes an optimal route through the candidate nodes using position-based particle swarm optimization. The proposed work is simulated using an NS2 simulator. Simulation results demonstrate that the method outperforms the standard routing algorithms in packet delivery fraction, end-to-end delay and execution time for routing in VANET scenarios

Opportunistic routing in wireless mesh networks

Advances in communication and networking technologies are rapidly making ubiquitous network connectivity a reality. In recent years, Wireless Mesh Networks (WMNs) have already become very popular and been receiving an increasing amount of attention by the research community. Basically, a WMN consists of simple mesh routers and mesh clients, where mesh routers form the backbone of WMN. Due to the limited transmission range of the radio, many pairs of nodes in WMN may not be able to communicate directly, hence they need other intermediate nodes to forward packets for them. Routing in such networks is an important issue and it poses great challenges. Opportunistic Routing (OR) has been investigated in recent years as a way to increase the performance of WMNs by exploiting its broadcast nature. In OR, in contrast to traditional routing, instead of pre-selecting a single specic node to be the next-hop as a forwarder for a packet, an ordered set of nodes (referred to as candidates) is selected as the potential next-hop forwarders. Thus, the source can use multiple potential paths to deliver the packets to the destination. More specically, when the current node transmits a packet, all the candidates that successfully receive it will coordinate with each other to determine which one will actually forward it, while the others will simply discard the packet. This dissertation studies the properties, performance, maximum gain, candidate selection algorithms and multicast delivery issues about Opportunistic Routing in WMNs. Firstly, we focus on the performance analysis of OR by proposing a Discrete Time Markov Chain (DTMC). This model can be used to evaluate OR in terms of expected number of transmissions from the source to the destination. Secondly, we apply our Markov model to compare relevant candidate selection algorithms that have been proposed in the literature. They range from non-optimum, but simple, to optimum, but with a high computational cost. Thirdly, the set of candidates which a node uses and priority order of them have a signicant impact on the performance of OR. Therefore, using a good metric and algorithm to select and order the candidates are key factors in designing an OR protocol. As the next contribution we propose a new metric that measures the expected distance progress of sending a packet using a set of candidates. Based on this metric we propose a candidate selection algorithm which its performance is very close to the optimum algorithm although our algorithm runs much faster. Fourthly, we have investigated the maximum gain that can be obtained using OR. We have obtained some equations that yield the distances of the candidates in OR such that the per transmission progress towards the destination is maximized. Based on these equations we have proposed a novel candidate selection algorithm. Our new algorithm only needs the geographical location of nodes. The performance of our proposal is very close to the optimum candidate selection algorithm although our algorithm runs much faster. Finally, using OR to support multicast is an other issue that we have investigated in this thesis. We do so by proposing a new multicast protocol which uses OR. Unlike traditional multicast protocols, there is no designated next-hop forwarder for each destination in our protocol, thus the delivery ratio is maximized by taking advantage of spatial diversity