Infrastructure Based Reactive Location Service for Packet Delivery in Vehicular Communication

VANETs are special kind of Mobile Ad Hoc Networks (MANETs) that are formed between moving vehicles on an as-needed basis. Routing in VANET uses a greedy routing protocol which requires geographical information like location of any vehicle. The primary objective of this paper is to reduce the transmission delay by using some Road Side Units (RSU) already deployed along the roads. RSU gather information about all the vehicles which are connected in its range. Here each and every vehicle need not be communicated but the vehicles that are nearest and which have the information about location of destination are only involved. We use enhanced RLS which is hybrid communication from source to destination. It results to reduce the flooding requests and make communication faster which leads to improve the packet delivery ratio and reduce the transmission delay or end to end delay. In addition to this the source vehicle sends a request with its velocity to RSU, it will communicate with other RSU’s for the destination vehicle. After finding the destination it will send the request with velocity of the destination. Based on the velocity of destination and intermediate nodes the source will increase its velocity to avoid the frequent link breakage in order to reduce the transmission delay. The proposed algorithm is simulated using NS2 and results shows that ERLS decreases the transmission delay and increases the packet delivery ratio.

Optimisation of the coalescent hyperbolic embedding of complex networks

Several observations indicate the existence of a latent hyperbolic space behind real networks that makes their structure very intuitive in the sense that the probability for a connection is decreasing with the hyperbolic distance between the nodes. A remarkable network model generating random graphs along this line is the popularity-similarity optimisation (PSO) model, offering a scale-free degree distribution, high clustering and the small-world property at the same time. These results provide a strong motivation for the development of hyperbolic embedding algorithms, that tackle the problem of finding the optimal hyperbolic coordinates of the nodes based on the network structure. A very promising recent approach for hyperbolic embedding is provided by the noncentered minimum curvilinear embedding (ncMCE) method, belonging to the family of coalescent embedding algorithms. This approach offers a high-quality embedding at a low running time. In the present work we propose a further optimisation of the angular coordinates in this framework that seems to reduce the logarithmic loss and increase the greedy routing score of the embedding compared to the original version, thereby adding an extra improvement to the quality of the inferred hyperbolic coordinates.

Modified fuzzy-based greedy routing protocol for VANETs

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

Hyperbolic mapping of human proximity networks

Human proximity networks are temporal networks representing the close-range proximity among humans in a physical space. They have been extensively studied in the past 15 years as they are critical for understanding the spreading of diseases and information among humans. Here we address the problem of mapping human proximity networks into hyperbolic spaces. Each snapshot of these networks is often very sparse, consisting of a small number of interacting (i.e., non-zero degree) nodes. Yet, we show that the time-aggregated representation of such systems over sufficiently large periods can be meaningfully embedded into the hyperbolic space, using methods developed for traditional (non-mobile) complex networks. We justify this compatibility theoretically and validate it experimentally. We produce hyperbolic maps of six different real systems, and show that the maps can be used to identify communities, facilitate efficient greedy routing on the temporal network, and predict future links with significant precision. Further, we show that epidemic arrival times are positively correlated with the hyperbolic distance from the infection sources in the maps. Thus, hyperbolic embedding could also provide a new perspective for understanding and predicting the behavior of epidemic spreading in human proximity systems.

Resilient greedy routing on GPS-free surface sensor networks

We design a greedy routing scheme specifically for GPS-free large-scale wireless sensor networks deployed on surfaces of complex-connected three-dimensional settings. Compared with other greedy embedding–based surface network routing scheme, the proposed one is cut free such that no pair of nodes suffers a long detour to reach each other. The routing scheme is designed to be resilient to node or link failures especially under random node or link failure model where each node in a network has an equal and independent probability of failure during some time interval. The proposed algorithm is fully distributed and scalable to both the size and the topological complexity of a network. Each sensor node requires only limited and constant storage. Simulation results show the proposed routing scheme with a higher successful delivery ratio, a lower average stretch factor, and a lower normalized communication cost compared with other resilient routing methods.

Hybrid on-demand greedy routing protocol with backtracking for mobile ad-hoc networks

Purpose The purpose of this paper is to design an efficient on-demand routing protocol for mobile ad hoc networks (MANETs) which combines greedy forwarding and backtracking. Design/methodology/approach It uses a hybrid approach. It uses greedy approach to determine a route from source to the destination. If the greedy approach fails, then it uses a backtracking approach. Combining greedy and backtracking approaches results in a more efficient protocol. Findings A new routing algorithm for MANETs which performs better than some of the existing algorithms. Research limitations/implications A major limitation of this work is that the authors did not implement the protocol on a test bed and evaluated the performance. They neither had the infrastructure nor the resources to actually implement the protocol. Instead, like most of the researchers, they evaluated the performance of their protocol based on extensive simulation. The mobility model, the area of deployment and the density of nodes chosen to simulate the protocol are consistent with what many of the other researchers have done. Intuitively, the authors’ protocol, as the performance evaluation indicates, is likely to perform well in small networks. Practical implications The authors did not implement the protocol on a test bed to evaluate the performance of the protocol. The authors used simulation to study the performance of their protocol. Their simulation model is similar to many of the research works published in the literature. Originality/value To the authors’ knowledge, no other paper has combined the greedy and backtracking approach to design a routing protocols for MANETs.