Message forwarding techniques in Bluetooth enabled opportunistic communication environment

These days, most of the mobile phones are smart enough with computer like intelligence and equipped with multiple communication technologies such as Bluetooth, wireless LAN, GPRS and GSM. Different communication medium on single device have unlocked the new horizon of communication means. Modern mobile phones are not only capable of using traditional way of communication via GSM or GPRS; but, also use wireless LANs using access points where available. Among these communication means, Bluetooth technology is very intriguing and unique in nature. Any two devices equipped with Bluetooth technology can communicate directly due to their unique IDs in the world. This is opposite to GSM or Wireless LAN technology; where devices are dependent on infrastructure of service providers and have to pay for their services. Due to continual advancement in the field of mobile technology, mobile ad-hoc network seems to be more realised than ever using Bluetooth. In traditional mobile ad-hoc networks (MANETs), before information sharing, devices have partial or full knowledge of routes to the destinations using ad-hoc routing protocols. This kind of communication can only be realised if nodes follow the certain pattern. However, in reality mobile ad-hoc networks are highly unpredictable, any node can join or leave network at any time, thus making them risky for effective communication. This issue is addressed by introducing new breed of ad-hoc networking, known as opportunistic networks. Opportunistic networking is a concept that is evolved from mobile ad-hoc networking. In opportunistic networks nodes have no prior knowledge of routes to intended destinations. Any node in the network can be used as potential forwarder with the exception of taking information one step closer to intended destination. The forwarding decision is based on the information gathered from the source node or encountering node. The opportunistic forwarding can only be achieved if message forwarding is carried out in store and forward fashion. Although, opportunistic networks are more flexible than traditional MANETs, however, due to little insight of network, it poses distinct challenges such as intermittent connectivity, variable delays, short connection duration and dynamic topology. Addressing these challenges in opportunistic network is the basis for developing new and efficient protocols for information sharing. The aim of this research is to design different routing/forwarding techniques for opportunistic networks to improve the overall message delivery at destinations while keeping the communication cost very low. Some assumptions are considered to improved directivity of message flow towards intended destinations. These assumptions exploit human social relationships analogies, approximate awareness of the location of nodes in the network and use of hybrid communication by combining several routing concept to gain maximum message directivity. Enhancement in message forwarding in opportunistic networks can be achieved by targeting key nodes that show high degree of influence, popularity or knowledge inside the network. Based on this observation, this thesis presents an improved version of Lobby Influence (LI) algorithm called as Enhanced Lobby Influence (ELI). In LI, the forwarding decision is based on two important factors, popularity of node and popularity of node’s neighbour. The forwarding decision of Enhanced Lobby Influence not only depends on the intermediate node selection criteria as defined in Lobby Influence but also based on the knowledge of previously direct message delivery of intended destination. An improvement can be observed if nodes are aware of approximate position of intended destinations by some communication means such as GPS, GSM or WLAN access points. With the knowledge of nodes position in the network, high message directivity can be achieved by using simple concepts of direction vectors. Based on this observation, this research presents another new algorithm named as Location-aware opportunistic content forwarding (LOC). Last but not least, this research presents an orthodox yet unexplored approach for efficient message forwarding in Bluetooth communication environment, named as Hybrid Content Forwarding (HCF). The new approach combines the characteristics of social centrality based forwarding techniques used in opportunistic networks with traditional MANETs protocols used in Bluetooth scatternets. Simulation results show that a significant increase in delivery radio and cost reduction during content forwarding is observed by deploying these proposed algorithms. Also, comparison with existing technique shows the efficiency of using the new schemes

Improving Link Prediction in Intermittently Connected Wireless Networks by Considering Link and Proximity Stabilities

Several works have outlined the fact that the mobility in intermittently connected wireless networks is strongly governed by human behaviors as they are basically human-centered. It has been shown that the users' moves can be correlated and that the social ties shared by the users highly impact their mobility patterns and hence the network structure. Tracking these correlations and measuring the strength of social ties have led us to propose an efficient distributed tensor-based link prediction technique. In fact, we are convinced that the feedback provided by such a prediction mechanism can enhance communication protocols such as opportunistic routing protocols. In this paper, we aim to bring out that measuring the stabilities of the link and the proximity at two hops can improve the efficiency of the proposed link prediction technique. To quantify these two parameters, we propose an entropy estimator in order to measure the two stability aspects over successive time periods. Then, we join these entropy estimations to the tensor-based link prediction framework by designing new prediction metrics. To assess the contribution of these entropy estimations in the enhancement of tensor-based link prediction efficiency, we perform prediction on two real traces. Our simulation results show that by exploiting the information corresponding to the link stability and/or to the proximity stability, the performance of the tensor-based link prediction technique is improved. Moreover, the results attest that our proposal's ability to outperform other well-known prediction metrics.Comment: Published in the proceedings of the 13th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), San Francisco, United States, 201

Spatial-temporal reasoning applications of computational intelligence in the game of Go and computer networks

Spatial-temporal reasoning is the ability to reason with spatial images or information about space over time. In this dissertation, computational intelligence techniques are applied to computer Go and computer network applications. Among four experiments, the first three are related to the game of Go, and the last one concerns the routing problem in computer networks. The first experiment represents the first training of a modified cellular simultaneous recurrent network (CSRN) trained with cellular particle swarm optimization (PSO). Another contribution is the development of a comprehensive theoretical study of a 2x2 Go research platform with a certified 5 dan Go expert. The proposed architecture successfully trains a 2x2 game tree. The contribution of the second experiment is the development of a computational intelligence algorithm calledcollective cooperative learning (CCL). CCL learns the group size of Go stones on a Go board with zero knowledge by communicating only with the immediate neighbors. An analysis determines the lower bound of a design parameter that guarantees a solution. The contribution of the third experiment is the proposal of a unified system architecture for a Go robot. A prototype Go robot is implemented for the first time in the literature. The last experiment tackles a disruption-tolerant routing problem for a network suffering from link disruption. This experiment represents the first time that the disruption-tolerant routing problem has been formulated with a Markov Decision Process. In addition, the packet delivery rate has been improved under a range of link disruption levels via a reinforcement learning approach --Abstract, page iv

Efficient route discovery for reactive routing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Information on the location of mobile nodes in Mobile Ad-hoc Networks (MANETs) has the potential to significantly improve network performance. This thesis uses node location information to develop new techniques for route discovery in on-demand routing protocols such as the Ad-hoc On-Demand Distance Vector (AODV), thus making an important contribution to enhancing the experience of using mobile networks. A Candidate Neighbours to Rebroadcast the Route Request (CNRR) approach has been proposed to reduce the deleterious impact, known as the broadcast storm, of RREQ packets flooding in traditional on-demand routing protocols. The main concept behind CNRR is specifying a set of neighbours which will rebroadcast the received RREQ. This is a departure from the traditional approach of all receiving nodes rebroadcasting RREQs and has the effect of reducing the problem of redundancy from which mobile networks suffer. The proposed protocol has been developed in two phases: Closest-CNRR and Furthest-CNRR. The simulation results show that the proposed algorithms have a significant effect as they reduce the routing overhead of the AODV protocol by up to 28% compared to the C-CNRR, and by up to 17.5% compared to the F-CNRR. Notably, the proposed algorithms simultaneously achieve better throughput and less data dropping. The Link Stability and Energy Aware protocol (LSEA) has been developed to reduce the overhead while increasing network lifetimes. The LSEA helps to control the global dissemination of RREQs in the network by eliminating those nodes that have a residual energy level below a specific threshold value from participation in end-to-end routes. The proposed LSEA protocol significantly increases network lifetimes by up to 19% compared with other on-demand routing protocols while still managing to obtain the same packet delivery ratio and network throughput levels. Furthermore, merging the LSEA and CNRR concepts has the great advantage of reducing the dissemination of RREQs in the network without loss of reachability among the nodes. This increases network lifetimes, reduces the overhead and increases the amount of data sent and received. Accordingly, a Position-based Selective Neighbour (PSN) approach has been proposed which combines the advantages of zoning and link stability. The results show that the proposed technique has notable advantages over both the AODV and MAAODV as it improves delivery ratios by 24.6% and 18.8%, respectively.Funded by National Council for Training - Sudan and the Sudan Academy of Science

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

Cost functions in optical burst-switched networks

Optical Burst Switching (OBS) is a new paradigm for an all-optical Internet. It combines the best features of Optical Circuit Switching (OCS) and Optical Packet Switching (OPS) while avoidmg the mam problems associated with those networks .Namely, it offers good granularity, but its hardware requirements are lower than those of OPS. In a backbone network, low loss ratio is of particular importance. Also, to meet varying user requirements, it should support multiple classes of service. In Optical Burst-Switched networks both these goals are closely related to the way bursts are arranged in channels. Unlike the case of circuit switching, scheduling decisions affect the loss probability of future burst This thesis proposes the idea of a cost function. The cost function is used to judge the quality of a burst arrangement and estimate the probability that this burst will interfere with future bursts. Two applications of the cost functio n are proposed. A scheduling algorithm uses the value of the cost function to optimize the alignment of the new burst with other bursts in a channel, thus minimising the loss ratio. A cost-based burst droppmg algorithm, that can be used as a part of a Quality of Service scheme, drops only those bursts, for which the cost function value indicates that are most likely to cause a contention. Simulation results, performed using a custom-made OBS extension to the ns-2 simulator, show that the cost-based algorithms improve network performanc