ENERGY CONSERVATION FOR WIRELESS AD HOC ROUTING

Self-configuring wireless ad hoc networks have attracted considerable attention in the last few years due to their valuable civil and military applications. One aspect of such networks that has been studied insufficiently is the energy efficiency. Energy efficiency is crucial to prolong the network lifetime and thus make the network more survivable.Nodes in wireless ad hoc networks are most likely to be driven by battery and hence operate on an extremely frugal energy budget. Conventional ad hoc routing protocols are focused on handling the mobility instead of energy efficiency. Energy efficient routing strategies proposed in literature either do not take advantage of sleep modes to conserve energy more efficiently, or incur much overhead in terms of control message and computing complexity to schedule sleep modes and thus are not scalable.In this dissertation, a novel strategy is proposed to manage the sleep of the nodes in the network so that energy can be conserved and network connectivity can be kept. The novelty of the strategy is its extreme simplicity. The idea is derived from the results of the percolation theory, typically called gossiping. Gossiping is a convenient and effective approach and has been successfully applied to several areas of the networking. In the proposed work, we will developa sleep management protocol from gossiping for both static and mobile wireless ad hoc networks. Then the protocol will be extended to the asynchronous network, where nodes manage their own states independently. Analysis and simulations will be conducted to show thecorrectness, effectiveness and efficiency of the proposed work. The comparison between analytical and simulation results will justify them for each other. We will investigate the most important performance aspects concerning the proposed strategy, including the effect ofparameter tuning and the impacts of routing protocols. Furthermore, multiple extensions will be developed to improve the performance and make the proposed strategy apply to different network scenarios

THE EFFECT OF INTERACTIONS BETWEEN PROTOCOLS AND PHYSICAL TOPOLOGIES ON THE LIFETIME OF WIRELESS SENSOR NETWORKS

Wireless sensor networks enable monitoring and control applications such weather sensing, target tracking, medical monitoring, road monitoring, and airport lighting. Additionally, these applications require long term and robust sensing, and therefore require sensor networks to have long system lifetime. However, sensor devices are typically battery operated. The design of long lifetime networks requires efficient sensor node circuits, architectures, algorithms, and protocols. In this research, we observed that most protocols turn on sensor radios to listen or receive data then make a decision whether or not to relay it. To conserve energy, sensor nodes should consider not listening or receiving the data when not necessary by turning off the radio. We employ a cross layer scheme to target at the network layer issues. We propose a simple, scalable, and energy efficient forwarding scheme, which is called Gossip-based Sleep Protocol (GSP). Our proposed GSP protocol is designed for large low-cost wireless sensor networks with low complexity to reduce the energy cost for every node as much as possible. The analysis shows that allowing some nodes to remain in sleep mode improves energy efficiency and extends network lifetime without data loss in the topologies such as square grid, rectangular grid, random grid, lattice topology, and star topology. Additionally, GSP distributes energy consumption over the entire network because the nodes go to sleep in a fully random fashion and the traffic forwarding continuously via the same path can be avoided

Asynchronous epidemic algorithms for consistency in large-scale systems

Achieving and detecting a globally consistent state is essential to many services in the large and extreme-scale distributed systems, especially when the desired consistent state is critical for services operation. Centralised and deterministic approaches for synchronisation and distributed consistency are not scalable and not fault-tolerant. Alternatively, epidemic-based paradigms are decentralised computations based on randomised communications. They are scalable, resilient, fault-tolerant, and converge to the desired target in logarithmic time with respect to system size. Thus, many distributed services have adopted epidemic protocols to achieve the consensus and the consistent state, mainly due to scalability concerns. The convergence of epidemic protocols is stochastically guaranteed. However, the detection of the convergence is probabilistic and non-explicit. In a real-world environment, systems are unreliable, and epidemic protocols cannot converge to the desired state. Thus, achieving convergence by itself does not ensure making a system-wide consistent state under dynamic conditions. The research work presented in this thesis introduces the Phase Transition Algorithm (PTA) to achieve distributed consistent state based on the explicit detection of convergence. Each phase in PTA is a decentralised decision-making process that implements epidemic data aggregation, in which the detection of convergence implies achieving a global agreement. The phases in PTA can be cascaded to achieve higher certainty as desired. Following the PTA, two epidemic protocols, namely PTP and ECP, are proposed to acquire of consensus, i.e. for the consistency in data dissemination and data aggregation. The protocols are examined through simulations, and experimental results have validated the protocols ability to achieve and explicitly detect the consensus among system nodes. The research work has also studied the epidemic data aggregation under nodes churn and network failures, in which the analysis has identified three phases of the aggregation process. The investigations have shown a different impact of nodes churn on each phase. The phase that is critical for the aggregation process has been studied further, which led to propose new robust data aggregation protocols, REAP and REAP+. Each protocol has a different decentralised replication method, and both implements distributed failure detection and instantaneous mass restoration mechanisms. Simulations have validated the protocols, and results have shown protocols ability to converge, detect convergence, and produce competitive accuracy under various levels of nodes churn. Furthermore, distributed consistency in continuous systems is addressed in the research. The work has proposed a novel continuous epidemic protocol with the adaptive restart mechanism. The protocol restarts either upon the detection of system convergence or upon the detection of divergence. Also, the protocol introduces the seed selection method for the peak data distribution in decentralised approaches, which was a challenge that requires single-point initialisation and leader-election step. The simulations validated the performance of the algorithm under static and dynamic conditions and approved that convergence and divergence detection accuracy can be tuned as desired. Finally, the research work shows that combining and integrating of the proposed protocols enables extreme-scale distributed systems to achieve and detect global consistent states even under realistic and dynamical conditions

Encounter gossip: a high coverage broadcast protocol for MANET

PhD ThesisMobile Ad-hoc Networks (MANETs) allow deployment of mobile wireless devices or nodes in a range of environments without any fixed infrastructure and hence at a minimal setup cost. Broadcast support that assures a high coverage (i.e., a large fraction of nodes receiving a broadcast) is essential for hosting user applications, and is also non-trivial to achieve due to the nature of devices and mobility. We propose Encounter Gossip, a novel broadcast protocol, which holds minimal state and is unaware of network topology. Coverage obtained can be made arbitrarily close to 1 at a moderate cost of extra message tra c, even in partition-prone networks. Under certain simplifying assumptions, it is shown that a high coverage is achieved by making a total of O(n ln n) broadcasts, where n is the number of nodes, and the time to propagate a message is O(ln n). The e ect of various network parameters on the protocol performance is examined. We then propose modifications to minimise the number of redundant transmissions without compromising the achieved coverage. Two approaches are pursued: timer based and history based. The e ectiveness of each of these approaches is assessed through an extensive set of simulation experiments in the context of two mobility models. Specifically, we introduce a new heuristic alpha policy which achieves significant reduction in redundancy with negligible reduction in coverage. A generalisation to multiple broadcasts proceeding in parallel is proposed and the protocol is refined to reduce problems that can occur due to the effects of high mobility when transmitting a large number of messages. Finally, we implement and validate Encounter Gossip in the context of a real-life mobile ad-hoc network. All these investigations suggest that the protocol, together with the proposed modifications and re nements, is suited to MANETs of varying degrees of node densities and speeds

INDIGO: a generalized model and framework for performance prediction of data dissemination

According to recent studies, an enormous rise in location-based mobile services is expected in future. People are interested in getting and acting on the localized information retrieved from their vicinity like local events, shopping offers, local food, etc. These studies also suggested that local businesses intend to maximize the reach of their localized offers/advertisements by pushing them to the maxi- mum number of interested people. The scope of such localized services can be augmented by leveraging the capabilities of smartphones through the dissemination of such information to other interested people. To enable local businesses (or publishers) of localized services to take in- formed decision and assess the performance of their dissemination-based localized services in advance, we need to predict the performance of data dissemination in complex real-world scenarios. Some of the questions relevant to publishers could be the maximum time required to disseminate information, best relays to maximize information dissemination etc. This thesis addresses these questions and provides a solution called INDIGO that enables the prediction of data dissemination performance based on the availability of physical and social proximity information among people by collectively considering different real-world aspects of data dissemination process. INDIGO empowers publishers to assess the performance of their localized dissemination based services in advance both in physical as well as the online social world. It provides a solution called INDIGO–Physical for the cases where physical proximity plays the fundamental role and enables the tighter prediction of data dissemination time and prediction of best relays under real-world mobility, communication and data dissemination strategy aspects. Further, this thesis also contributes in providing the performance prediction of data dissemination in large-scale online social networks where the social proximity is prominent using INDIGO–OSN part of the INDIGO framework under different real-world dissemination aspects like heterogeneous activity of users, type of information that needs to be disseminated, friendship ties and the content of the published online activities. INDIGO is the first work that provides a set of solutions and enables publishers to predict the performance of their localized dissemination based services based on the availability of physical and social proximity information among people and different real-world aspects of data dissemination process in both physical and online social networks. INDIGO outperforms the existing works for physical proximity by providing 5 times tighter upper bound of data dissemination time under real-world data dissemination aspects. Further, for social proximity, INDIGO is able to predict the data dissemination with 90% accuracy and differently, from other works, it also provides the trade-off between high prediction accuracy and privacy by introducing the feature planes from an online social networks

Neighbor discovery in multi-hop wireless networks: evaluation and dimensioning with interferences considerations

International audienceIn this paper, we study the impact of collisions and interferences on a neighbor discovery process in the context of multi-hop wireless networks. We consider three models in which interferences and collisions are handled in very different ways. From an ideal channel where simultaneous transmissions do not interfere, we derive an alternate channel where simultaneous transmissions are considered two-by-two under the form of collisions, to finally reach a more realistic channel where simultaneous transmissions are handled under the form of shot-noise interferences. In these models, we analytically compute the link probability success between two neighbors as well as the expected number of nodes that correctly receive a Hello packet. Using this analysis, we show that if the neighbor discovery process is asymptotically equivalent in the three models, it offers very different behaviors locally in time. In particular, the scalability of the process is not the same depending on the way interferences are handled. Finally, we apply our results to the dimensioning of a Hello protocol parameters. We propose a method to adapt the protocol parameters to meet application constraints on the neighbor discovery process and to minimize the protocol energy consumption

Journal of Telecommunications and Information Technology, 2009, nr 2

kwartalni

Models, services and security in modern online social networks

Modern online social networks have revolutionized the world the same way the radio and the plane did, crossing geographical and time boundaries, not without problems, more can be learned, they can still change our world and that their true worth is still a question for the future