Modeling and comparison of candidate selection algorithms in opportunistic routing

Opportunistic Routing (OR) has been investigated in recent years as a way to increase the performance of multihop wireless networks by exploiting its broadcast nature. In contrast to traditional routing, where traffic is sent along pre-determined paths, in OR an ordered set of candidates is selected for each next-hop. Upon each transmission, the candidates coordinate such that the most priority one receiving the packet actually forwards it. Most of the research in OR has been addressed to investigate candidate selection algorithms. In this paper we propose a discrete time Markov chain to assess the improvement that may be achieved using opportunistic routing. We use our model to compare a selected group of candidate selection algorithms that have been proposed in the literature. Our main conclusion is that optimality is obtained at a high computational cost, with a performance gain very similar to that of much simpler but non-optimal algorithms. Therefore, we conclude that fast and simple OR candidate selection algorithms may be preferable in dynamic networks, where the candidates sets are likely to be updated frequently. © 2011 Elsevier B.V. All rights reserved.This work was supported by the Spanish government through projects TIN2010-21378-C02-01 and TIN2010-21378-C02-02, by the Generalitat de Catalunya through project 2009-SGR-1167, and by the European Commission through the NoE EuroNF.Darehshoorzadeh, A.; Cerdà-Alabern, L.; Pla, V. (2011). Modeling and comparison of candidate selection algorithms in opportunistic routing. Computer Networks. 55(13):2886-2898. https://doi.org/10.1016/j.comnet.2011.06.009S28862898551

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

Opportunistic routing in wireless mesh networks

Opportunistic Routing (OR) has been proposed as a way to increase the performance of wireless networks by exploiting its broadcast nature. In OR, instead of pre-selecting a single specific node to be the next-hop as a forwarder for a packet, multiple nodes can potentially be selected as the next-hop forwarder. Thus the source can use multiple potential paths to deliver the packets to the destination. More specially, when the current node transmits a packet, all the candidates that receive the packet successfully will coordinate with each other to determine which one would actually forward the packet according to some criteria, while the other nodes will simply discard the packet. In this chapter, we survey the state of the art in OR, then focus on the candidates selection algorithms and carry out a comparative performance evaluation of the most relevant proposals appeared in the literature.Peer ReviewedPostprint (author’s final draft

Candidate Selection Algorithms in Opportunistic Routing based on Distance Progress

Opportunistic Routing (OR) is a new class of routing protocols that selects the next-hop forwarder on-the-fly. In contrast to traditionally routing, OR does not select a single node as the next-hop forwarder, but a set of forwarder candidates. When a packet is transmitted, the candidates coordinate such that the best one receiving the packet will forward it, while the others will discard the packet. The selection and prioritization of candidates, referred to as candidate selection algorithm, has a great impact on OR performance. In this paper we propose and study two new candidate selection algorithms based on the geographic position of nodes. This information is used by the candidate selection algorithms in order to maximize the distance progress towards the destination. We compare our proposals with other well-known candidate selection algorithms proposed in the literature through mathematical analysis and simulation. We show that candidate selection algorithms based on distance progress achieve almost the same performance as the optimum algorithms proposed in the literature, while the computational cost is dramatically reduced.Darehshoorzadeh, A.; Cerdà-Alabern, L.; Pla, V. (2015). Candidate Selection Algorithms in Opportunistic Routing based on Distance Progress. International Journal of Ad Hoc and Ubiquitous Computing. 20(3):137-147. doi:10.1504/IJAHUC.2015.073168S13714720

Design and analysis of a beacon-less routing protocol for large volume content dissemination in vehicular ad hoc networks

Largevolumecontentdisseminationispursuedbythegrowingnumberofhighquality applications for Vehicular Ad hoc NETworks(VANETs), e.g., the live road surveillance service and the video-based overtaking assistant service. For the highly dynamical vehicular network topology, beacon-less routing protocols have been proven to be efficient in achieving a balance between the system performance and the control overhead. However, to the authors’ best knowledge, the routing design for large volume content has not been well considered in the previous work, which will introduce new challenges, e.g., the enhanced connectivity requirement for a radio link. In this paper, a link Lifetime-aware Beacon-less Routing Protocol (LBRP) is designed for large volume content delivery in VANETs. Each vehicle makes the forwarding decision based on the message header information and its current state, including the speed and position information. A semi-Markov process analytical model is proposed to evaluate the expected delay in constructing one routing path for LBRP. Simulations show that the proposed LBRP scheme outperforms the traditional dissemination protocols in providing a low end-to-end delay. The analytical model is shown to exhibit a good match on the delay estimation with Monte Carlo simulations, as well

Joint Congestion and Contention Avoidance in a Scalable QoS-Aware Opportunistic Routing in Wireless Ad-Hoc Networks

Opportunistic routing (OR) can greatly increase transmission reliability and network throughput in wireless ad-hoc networks by taking advantage of the broadcast nature of the wireless medium. However, network congestion is a barrier in the way of OR\u27s performance improvement, and network congestion control is a challenge in OR algorithms, because only the pure physical channel conditions of the links are considered in forwarding decisions. This paper proposes a new method to control network congestion in OR, considering three types of parameters, namely, the backlogged traffic, the traffic flows\u27 Quality of Service (QoS) level, and the channel occupancy rate. Simulation results show that the proposed algorithm outperforms the state-of-the-art algorithms in the context of OR congestion control in terms of average throughput, end-to-end delay, and Packet Delivery Ratio (PDR). Due to the higher PDR at different traffic loads and different node densities, it can be concluded that the proposed algorithm also improves network scalability, which is very desirable given the recent changes in wireless networks