85,476 research outputs found
Using genetic algorithms to optimise Wireless Sensor Network design
Wireless Sensor Networks(WSNs) have gained a lot of attention because of their potential to immerse deeper into people' lives. The applications of WSNs range from small home environment networks to large habitat monitoring. These highly diverse scenarios impose different requirements on WSNs and lead to distinct design and implementation decisions. This thesis presents an optimization framework for WSN design which selects a proper set of protocols and number of nodes before a practical network
deployment. A Genetic Algorithm(GA)-based Sensor Network Design Tool(SNDT) is proposed in this work for wireless sensor network design in terms of performance, considering application-specific requirements, deployment constrains and energy characteristics. SNDT relies on offine simulation analysis to help resolve design decisions. A GA is used as the optimization tool of the proposed system and an appropriate fitness function is derived to incorporate many aspects of network performance. The configuration attributes optimized by SNDT comprise the communication protocol selection and the number of nodes deployed in a fixed area. Three specific cases : a periodic-measuring application, an event detection type of application and a tracking-based application are considered to demonstrate and assess how the proposed framework performs. Considering the initial requirements of each case, the solutions provided by SNDT were proven to be favourable in terms of energy consumption, end-to-end delay and loss. The user-defined application requirements were successfully achieved
Secure Cloud Communication for Effective Cost Management System through MSBE
In Cloud Computing Architecture, Brokers are responsible to provide services
to the end users. An Effective Cost Management System (ECMS) which works over
Secure Cloud Communication Paradigm (SCCP) helps in finding a communication
link with overall minimum cost of links. We propose an improved Broker Cloud
Communication Paradigm (BCCP) with integration of security issues. Two
algorithms are included, first is Secure Optimized Route Cost Finder (S-ORCF)
to find optimum route between broker and cloud on the behalf of cost factor and
second is Secure Optimized Route Management (S-ORM) to maintain optimum route.
These algorithms proposed with cryptographic integrity of the secure route
discovery process in efficient routing approaches between broker and cloud.
There is lack in Dynamic Source Routing Approach to verify whether any
intermediate node has been deleted, inserted or modified with no valid
authentication. We use symmetric cryptographic primitives, which is made
possible due to multisource broadcast encryption scheme. This paper outlines
the use of secure route discovery protocol (SRDP)that employs such a security
paradigm in cloud computing.Comment: 12 pages, 3 figures, International Journal on Cloud Computing:
Services and Architecture(IJCCSA),Vol.2, No.3, June 201
A GA-based simulation system for WMNs: comparison analysis for different number of flows, client distributions, DCF and EDCA functions
In this paper, we compare the performance of Distributed Coordination Function (DCF) and Enhanced Distributed Channel Access (EDCA) for normal and uniform distributions of mesh clients considering two Wireless Mesh Network (WMN) architectures. As evaluation metrics, we consider throughput, delay, jitter and fairness index metrics. For simulations, we used WMN-GA simulation system, ns-3 and Optimized Link State Routing. The simulation results show that for normal distribution, the throughput of I/B WMN is higher than Hybrid WMN architecture. For uniform distribution, in case of I/B WMN, the throughput of EDCA is a little bit higher than Hybrid WMN. However, for Hybrid WMN, the throughput of DCF is higher than EDCA. For normal distribution, the delay and jitter of Hybrid WMN are lower compared with I/B WMN. For uniform distribution, the delay and jitter of both architectures are almost the same. However, in the case of DCF for 20 flows, the delay and jitter of I/B WMN are lower compared with Hybrid WMN. For I/B architecture, in case of normal distribution the fairness index of DCF is higher than EDCA. However, for Hybrid WMN, the fairness index of EDCA is higher than DCF. For uniform distribution, the fairness index of few flows is higher than others for both WMN architectures.Peer ReviewedPostprint (author's final draft
A Review on Biological Inspired Computation in Cryptology
Cryptology is a field that concerned with cryptography and cryptanalysis. Cryptography, which is a key technology in providing a secure transmission of information, is a study of designing strong cryptographic algorithms, while cryptanalysis is a study of breaking the cipher. Recently biological approaches provide inspiration in solving problems from various fields. This paper reviews major works in the application of biological inspired computational (BIC) paradigm in cryptology. The paper focuses on three BIC approaches, namely, genetic algorithm (GA), artificial neural network (ANN) and artificial immune system (AIS). The findings show that the research on applications of biological approaches in cryptology is minimal as compared to other fields. To date only ANN and GA have been used in cryptanalysis and design of cryptographic primitives and protocols. Based on similarities that AIS has with ANN and GA, this paper provides insights for potential application of AIS in cryptology for further research
Genetic Algorithm-based Mapper to Support Multiple Concurrent Users on Wireless Testbeds
Communication and networking research introduces new protocols and standards
with an increasing number of researchers relying on real experiments rather
than simulations to evaluate the performance of their new protocols. A number
of testbeds are currently available for this purpose and a growing number of
users are requesting access to those testbeds. This motivates the need for
better utilization of the testbeds by allowing concurrent experimentations. In
this work, we introduce a novel mapping algorithm that aims to maximize
wireless testbed utilization using frequency slicing of the spectrum resources.
The mapper employs genetic algorithm to find the best combination of requests
that can be served concurrently, after getting all possible mappings of each
request via an induced sub-graph isomorphism stage. The proposed mapper is
tested on grid testbeds and randomly generated topologies. The solution of our
mapper is compared to the optimal one, obtained through a brute-force search,
and was able to serve the same number of requests in 82.96% of testing
scenarios. Furthermore, we show the effect of the careful design of testbed
topology on enhancing the testbed utilization by applying our mapper on a
carefully positioned 8-nodes testbed. In addition, our proposed approach for
testbed slicing and requests mapping has shown an improved performance in terms
of total served requests, about five folds, compared to the simple allocation
policy with no slicing.Comment: IEEE Wireless Communications and Networking Conference (WCNC) 201
Coverage Protocols for Wireless Sensor Networks: Review and Future Directions
The coverage problem in wireless sensor networks (WSNs) can be generally
defined as a measure of how effectively a network field is monitored by its
sensor nodes. This problem has attracted a lot of interest over the years and
as a result, many coverage protocols were proposed. In this survey, we first
propose a taxonomy for classifying coverage protocols in WSNs. Then, we
classify the coverage protocols into three categories (i.e. coverage aware
deployment protocols, sleep scheduling protocols for flat networks, and
cluster-based sleep scheduling protocols) based on the network stage where the
coverage is optimized. For each category, relevant protocols are thoroughly
reviewed and classified based on the adopted coverage techniques. Finally, we
discuss open issues (and recommend future directions to resolve them)
associated with the design of realistic coverage protocols. Issues such as
realistic sensing models, realistic energy consumption models, realistic
connectivity models and sensor localization are covered
Genetic algorithms with elitism-based immigrants for dynamic shortest path problem in mobile ad hoc networks
This article is posted here with permission from the IEEE - Copyright @ 2009 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless sensor network (WSN), etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP problem turns out to be a dynamic optimization problem (DOP) in MANETs. In this paper, we propose to use elitism-based immigrants GA (EIGA) to solve the dynamic SP problem in MANETs. We consider MANETs as target systems because they represent new generation wireless networks. The experimental results show that the EIGA can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1
- âŠ