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Dynamic load balancing algorithm complexity
This paper presents a theoretical analysis of the asymptotic complexity inherent in a load balancing algorithm in a loosely-coupled network, where processor communication is achieved by message passing. The load balancing complexity depends on the network topology and the overhead of processor communication for each polling strategy. The best, worst, and average case analysis of the load balancing algorithms for the various polling topologies are presented. The polling strategies considered are local, global, and random polling. The complexity is presented as a function of the number of processors in the network
An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks
A high degree of reliability for critical data transmission is required in
body sensor networks (BSNs). However, BSNs are usually vulnerable to channel
impairments due to body fading effect and RF interference, which may
potentially cause data transmission to be unreliable. In this paper, an
adaptive and flexible fault-tolerant communication scheme for BSNs, namely
AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to
provide reliable data transmission when channel impairments occur. In order to
fulfill the reliability requirements of critical sensors, fault-tolerant
priority and queue are employed to adaptively adjust the channel bandwidth
allocation. Simulation results show that AFTCS can alleviate the effect of
channel impairments, while yielding lower packet loss rate and latency for
critical sensors at runtime.Comment: 10 figures, 19 page
Dynamic load balancing for the distributed mining of molecular structures
In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of
methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the
past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially
render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to
discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no
reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic
partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated
load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer
Institute’s HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed
approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable
for large-scale, multi-domain, heterogeneous environments, such as computational grids
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
E-Voting in an ubicomp world: trust, privacy, and social implications
The advances made in technology have unchained the user from the desktop into interactions where access is anywhere, anytime. In addition, the introduction of ubiquitous computing (ubicomp) will see further changes in how we interact with technology and also socially. Ubicomp evokes a near future in which humans will be surrounded by “always-on,” unobtrusive, interconnected intelligent objects where information is exchanged seamlessly. This seamless exchange of information has vast social implications, in particular the protection and management of personal information. This research project investigates the concepts of trust and privacy issues specifically related to the exchange of e-voting information when using a ubicomp type system
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