903 research outputs found
Fair Coalitions for Power-Aware Routing in Wireless Networks
Several power aware routing schemes have been developed under the assumption that nodes are willing to sacrifice their power reserves in the interest of the network as a whole. But, in several applications of practical utility, nodes are organized in groups, and as a result a node is willing to sacrifice in the interest of other nodes in its group but not necessarily for nodes outside its group. Such groups arise naturally as sets of nodes associated with a single owner or task. We consider the premise that groups will share resources with other groups only if each group experiences a reduction in power consuption. When this is the case the groups may form a coalition in which they route each other\u27s packets. We demonstrate that sharing between groups has different properties from sharing between individuals and investigate fair mutually-beneficial sharing between groups. In particular, we propose a pareto-efficient condition for group sharing based on max-min fairness called fair coalition routing. We propose distributed algorithms for computing the fair coalition routing. Using these algorithms we demonstrate that fair coalition routing allows different groups to mutually benefecially share their resources
Fair Coalitions for Power-Aware Routing in Wireless Networks
Several power-aware routing schemes have been developed for wireless networks under the assumption that nodes are willing to sacrifice their power reserves in the interest of the network as a whole. But, in several applications of practical utility, nodes are organized in groups, and as a result, a node is willing to sacrifice in the interest of other nodes in its group but not necessarily for nodes outside its group. Such groups arise naturally as sets of nodes associated with a single owner or task. We consider the premise that groups will share resources with other groups only if each group experiences a reduction in power consumption. Then, the groups may form a coalition in which they route each other’s packets. We demonstrate that sharing between groups has different properties from sharing between individuals and investigate fair, mutually beneficial sharing between groups. In particular, we propose a paretoefficient condition for group sharing based on max-min fairness called fair coalition routing. We propose distributed algorithms for computing the fair coalition routing. Using these algorithms, we demonstrate that fair coalition routing allows different groups to mutually beneficially share their resources
Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents
Autonomous wireless agents such as unmanned aerial vehicles or mobile base
stations present a great potential for deployment in next-generation wireless
networks. While current literature has been mainly focused on the use of agents
within robotics or software applications, we propose a novel usage model for
self-organizing agents suited to wireless networks. In the proposed model, a
number of agents are required to collect data from several arbitrarily located
tasks. Each task represents a queue of packets that require collection and
subsequent wireless transmission by the agents to a central receiver. The
problem is modeled as a hedonic coalition formation game between the agents and
the tasks that interact in order to form disjoint coalitions. Each formed
coalition is modeled as a polling system consisting of a number of agents which
move between the different tasks present in the coalition, collect and transmit
the packets. Within each coalition, some agents can also take the role of a
relay for improving the packet success rate of the transmission. The proposed
algorithm allows the tasks and the agents to take distributed decisions to join
or leave a coalition, based on the achieved benefit in terms of effective
throughput, and the cost in terms of delay. As a result of these decisions, the
agents and tasks structure themselves into independent disjoint coalitions
which constitute a Nash-stable network partition. Moreover, the proposed
algorithm allows the agents and tasks to adapt the topology to environmental
changes such as the arrival/removal of tasks or the mobility of the tasks.
Simulation results show how the proposed algorithm improves the performance, in
terms of average player (agent or task) payoff, of at least 30.26% (for a
network of 5 agents with up to 25 tasks) relatively to a scheme that allocates
nearby tasks equally among agents.Comment: to appear, IEEE Transactions on Mobile Computin
A Coalition-Formation Game Model for Energy-Efficient Routing in Mobile Ad-hoc Network
One of the most routing problems in Mobile Ad-hoc Network is the node’s selfishness. Nodes are generally selfish and try to maximize their own benefit; hence these nodes refuse to forward packet on behalf of others to preserve their limited energy resources. This selfishness may lead to a low efficiency of routing. Therefore, it is important to study mechanisms which can be used encourage cooperation among nodes, to maintain the network efficiency. In this paper, we propose a cooperative game theoretic model to support more energy-aware and available bandwidth routing in MANET. We introduce a novel framework from coalitional-formation game theory, called hedonic coalition-formation game. We integrate this model to OLSR protocol that is an optimization over the classical link state protocol for the MANETs. Within each coalition, a coalition coordinator acts as a special MPR node to improve the energy efficient and the packet success rate of the transmission. Simulation results show how the proposed algorithm improve the performance in terms of the percentage of selected MPR nodes in the network, the percentage of alive nodes by time, and the Packet Delivery Ratio. Which prove that our proposed model leads, to better results compared to the classical OLSR
Energy efficient cooperative coalition selection in cluster-based capillary networks for CMIMO IoT systems
The Cooperative Multiple-input-multiple-output (CMIMO) scheme has been suggested to extend the lifetime of cluster heads (CHs) in cluster-based capillary networks in Internet of Things (IoT) systems. However, the CMIMO scheme introduces extra energy overhead to cooperative devices and further reduces the lifetime of these devices. In this paper, we first articulate the problem of cooperative coalition’s selection for CMIMO scheme to extend the average battery capacity among the whole network, and then propose to apply the quantum-inspired particle swarm optimization (QPSO) to select the optimum cooperative coalitions of each hop in the routing path. Simulation results proved that the proposed QPSO-based cooperative coalition’s selection scheme could select the optimum cooperative sender and receiver devices in every hop dynamically and outperform the virtual MIMO scheme with a fixed number of cooperative devices
Energy aware and privacy preserving protocols for ad hoc networks with applications to disaster management
Disasters can have a serious impact on the functioning of communities and societies. Disaster management aims at providing efficient utilization of resources during pre-disaster (e.g. preparedness and prevention) and post-disaster (e.g. recovery and relief) scenarios to reduce the impact of disasters. Wireless sensors have been extensively used for early detection and prevention of disasters. However, the sensor\u27s operating environment may not always be congenial to these applications. Attackers can observe the traffic flow in the network to determine the location of the sensors and exploit it. For example, in intrusion detection systems, the information can be used to identify coverage gaps and avoid detection. Data source location privacy preservation protocols were designed in this work to address this problem.
Using wireless sensors for disaster preparedness, recovery and relief operations can have high deployment costs. Making use of wireless devices (e.g. smartphones and tablets) widely available among people in the affected region is a more practical approach. Disaster preparedness involves dissemination of information among the people to make them aware of the risks they will face in the event of a disaster and how to actively prepare for them. The content is downloaded by the people on their smartphones and tablets for ubiquitous access. As these devices are primarily constrained by their available energy, this work introduces an energy-aware peer-to-peer file sharing protocol for efficient distribution of the content and maximizing the lifetime of the devices. Finally, the ability of the wireless devices to build an ad hoc network for capturing and collecting data for disaster relief and recovery operations was investigated. Specifically, novel energy-adaptive mechanisms were designed for autonomous creation of the ad hoc network, distribution of data capturing task among the devices, and collection of data with minimum delay --Abstract, page iii
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