324 research outputs found
Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks
This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field
Applications of Repeated Games in Wireless Networks: A Survey
A repeated game is an effective tool to model interactions and conflicts for
players aiming to achieve their objectives in a long-term basis. Contrary to
static noncooperative games that model an interaction among players in only one
period, in repeated games, interactions of players repeat for multiple periods;
and thus the players become aware of other players' past behaviors and their
future benefits, and will adapt their behavior accordingly. In wireless
networks, conflicts among wireless nodes can lead to selfish behaviors,
resulting in poor network performances and detrimental individual payoffs. In
this paper, we survey the applications of repeated games in different wireless
networks. The main goal is to demonstrate the use of repeated games to
encourage wireless nodes to cooperate, thereby improving network performances
and avoiding network disruption due to selfish behaviors. Furthermore, various
problems in wireless networks and variations of repeated game models together
with the corresponding solutions are discussed in this survey. Finally, we
outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference
Mobile Ad-Hoc Networks
Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks
DRIFT: Efficient message ordering in ad hoc networks using virtual flooding
We present DRIFT --- a total order multicast algorithm for ad hoc networks with mobile or static nodes. Due to the ad hoc nature of the network, DRIFT uses flooding for message propagation. The key idea of DRIFT is virtual flooding --- a way of using unrelated message streams to propagate message causality information in order to accelerate message delivery. We describe DRIFT in detail. We evaluate its performance in a simulator and in a wireless sensor network. In both cases our results demonstrate that the performance of DRIFT exceeds that of the simple total order multicast algorithm designed for wired networks, on which it is based. In simulation at scale, for certain experiment settings, DRIFT achieved speedup of several orders of magnitude
A survey of flooding, gossip routing, and related schemes for wireless multi- hop networks
Flooding is an essential and critical service in computer networks that is
used by many routing protocols to send packets from a source to all nodes in
the network. As the packets are forwarded once by each receiving node, many
copies of the same packet traverse the network which leads to high redundancy
and unnecessary usage of the sparse capacity of the transmission medium.
Gossip routing is a well-known approach to improve the flooding in wireless
multi-hop networks. Each node has a forwarding probability p that is either
statically per-configured or determined by information that is available at
runtime, e.g, the node degree. When a packet is received, the node selects a
random number r. If the number r is below p, the packet is forwarded and
otherwise, in the most simple gossip routing protocol, dropped. With this
approach the redundancy can be reduced while at the same time the reachability
is preserved if the value of the parameter p (and others) is chosen with
consideration of the network topology. This technical report gives an overview
of the relevant publications in the research domain of gossip routing and
gives an insight in the improvements that can be achieved. We discuss the
simulation setups and results of gossip routing protocols as well as further
improved flooding schemes. The three most important metrics in this
application domain are elaborated: reachability, redundancy, and management
overhead. The published studies used simulation environments for their
research and thus the assumptions, models, and parameters of the simulations
are discussed and the feasibility of an application for real world wireless
networks are highlighted. Wireless mesh networks based on IEEE 802.11 are the
focus of this survey but publications about other network types and
technologies are also included. As percolation theory, epidemiological models,
and delay tolerant networks are often referred as foundation, inspiration, or
application of gossip routing in wireless networks, a brief introduction to
each research domain is included and the applicability of the particular
models for the gossip routing is discussed
Optimization of Mobility Parameters using Fuzzy Logic and Reinforcement Learning in Self-Organizing Networks
In this thesis, several optimization techniques for next-generation wireless networks are proposed to solve different problems in the field of Self-Organizing Networks and heterogeneous networks. The common basis of these problems is that network parameters are automatically tuned to deal with the specific problem. As the set of network parameters is extremely large, this work mainly focuses on parameters involved in mobility management. In addition, the proposed self-tuning schemes are based on Fuzzy Logic Controllers (FLC), whose potential lies in the capability to express the knowledge in a similar way to the human perception and reasoning. In addition, in those cases in which a mathematical approach has been required to optimize the behavior of the FLC, the selected solution has been Reinforcement Learning, since this methodology is especially appropriate for learning from interaction, which becomes essential in complex systems such as wireless networks.
Taking this into account, firstly, a new Mobility Load Balancing (MLB) scheme is proposed to solve persistent congestion problems in next-generation wireless networks, in particular, due to an uneven spatial traffic distribution, which typically leads to an inefficient usage of resources. A key feature of the proposed algorithm is that not only the parameters are optimized, but also the parameter tuning strategy. Secondly, a novel MLB algorithm for enterprise femtocells scenarios is proposed. Such scenarios are characterized by the lack of a thorough deployment of these low-cost nodes, meaning that a more efficient use of radio resources can be achieved by applying effective MLB schemes. As in the previous problem, the optimization of the self-tuning process is also studied in this case. Thirdly, a new self-tuning algorithm for Mobility Robustness Optimization (MRO) is proposed. This study includes the impact of context factors such as the system load and user speed, as well as a proposal for coordination between the designed MLB and MRO functions. Fourthly, a novel self-tuning algorithm for Traffic Steering (TS) in heterogeneous networks is proposed. The main features of the proposed algorithm are the flexibility to support different operator policies and the adaptation capability to network variations. Finally, with the aim of validating the proposed techniques, a dynamic system-level simulator for Long-Term Evolution (LTE) networks has been designed
Mobility prediction and multicasting in wireless networks : performance and analysis
Handoff is a call handling mechanism that is invoked when a mobile node moves from one cell to another. Such movement may lead to degradation in performance for wireless networks as a result of packet losses. A promising technique proposed in this thesis is to apply multicasting techniques aided by mobility prediction in order to improve handoff performance. In this thesis, we present a method that uses a Grey model for mobility prediction and a fuzzy logic controller that has been fine-tuned using evolutionary algorithms in order to improve prediction accuracy. We also compare the self-tuning algorithm with two evolutionary algorithms in terms of accuracy and their convergence times. Our proposed method takes into account signal strengths from the base stations and predicts the signal strength of the next candidate base station in order to provide improved handover performance. The primary decision for mobility prediction is the accurate prediction of signal strengths obtained from the base stations and remove any unwanted errors in the prediction using suitable optimisation techniques. Furthermore, the model includes the procedures of fine-tuning the predicted data using fuzzy parameters. We also propose suitable multicasting algorithms to minimise the reservation of overall network resource requirements during handoff with the mobility prediction information. To be able to efficiently solve the problem, the situation is modelled using a multicast tree that is defined to maintain connectivity with the mobile node, whilst ensuring bandwidth guarantees and a minimum hop-count. In this approach, we have tried to solve the problem by balancing two objectives through putting a weight on each of two costs. We provide a detailed description of an algorithm to implement join and prune mechanisms, which will help to build an optimal multicast tree with QoS requirements during handoff as well as incorporating dynamic changes in the positions of mobile nodes. An analysis of how mobility prediction helps in the selection of potential Access Routers (AR) with QoS requirements - which affects the multicast group size and bandwidth cost of the multicast tree -- is presented. The proposed technique tries to minimise the number of multicast tree join and prune operations. Our results show that the expected size of the multicast group increases linearly with an increase in the number of selected destination AR's for multicast during handoff. We observe that the expected number of joins and prunes from the multicast tree increases with group size. A special simulation model was developed to demonstrate both homogeneous and heterogeneous handoff which is an emerging requirement for fourth generation mobile networks. The model incorporates our mobility prediction model for heterogeneous handoff between the Wireless LAN and a cellular network. The results presented in this thesis for mobility prediction, multicasting techniques and heterogeneous handoff include proposed algorithms and models which aid in the understanding, analysing and reducing of overheads during handoff
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