{"title":"Improving the performance of TAntNet-2 by using multi forward scouts","authors":"Ayman M. Ghazy, H. Hefny","doi":"10.1109/ICCES.2015.7393010","DOIUrl":"https://doi.org/10.1109/ICCES.2015.7393010","url":null,"abstract":"Dynamic Traffic Routing System is an important intelligent transport system that is used to direct vehicles to good routes and consequently reduce congestion on the road network. The performance of dynamic routing system depends on a dynamic routing algorithm. AntNet algorithm is a routing algorithm inspired from the foraging behavior of ants. TAntNet is a family of dynamic routing algorithms that uses a threshold travel time to enhance the performance of AntNet algorithm when applied to traffic road networks. This paper presents new improvements on TAntNet algorithms. The new improving TAntNet algorithm uses Multi forward agents instead of one compared with AntNet and TAntNet-2. The new technique saves the discovered routes of each of the forward agents and the corresponding backward ant uses the best of them. Experiments showed better performance for the proposed new mechanism of launching multi forward agents for each single agent compared with the old mechanisms of launching only one forward agent for each backward agent.","PeriodicalId":227813,"journal":{"name":"2015 Tenth International Conference on Computer Engineering & Systems (ICCES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124335640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling and optimization of energy consumption in Wireless Sensor Networks","authors":"M. Abo-Zahhad, M. Farrag, Abdelhay Ali","doi":"10.1109/ICCES.2015.7393063","DOIUrl":"https://doi.org/10.1109/ICCES.2015.7393063","url":null,"abstract":"Energy consumption and energy modeling are important issues in designing and implementing of Wireless Sensor Networks (WSNs), which help the designers to optimize the energy consumption in WSN nodes. Good knowledge of the sources of energy consumption in WSNs is the first step to reduce energy consumption. Therefore, an accurate energy model is required for the evaluation of communication protocols. In this paper, an energy model for WSNs is provided considering the physical layer and MAC layer parameters by determining the energy consumed per payload bit transferred without error over AWGN channel. This model has been tested with real data and and NS-2 simulator. Results show good agreement between proposed model, experimental measurements and NS-2 simulator with mean absolute percentage error less than 5.18%. Furthermore, the proposed model is exploited to optimize transmitted power to achieve minimum energy consumption. Finally, a closed-form expression for optimum transmitted power is derived for M-QAM modulation scheme.","PeriodicalId":227813,"journal":{"name":"2015 Tenth International Conference on Computer Engineering & Systems (ICCES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129217558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hard decision Cooperative Spectrum Sensing based on estimating the noise uncertainty factor","authors":"Hossam M. Farag, E. M. Mohamed","doi":"10.1109/ICCES.2015.7393049","DOIUrl":"https://doi.org/10.1109/ICCES.2015.7393049","url":null,"abstract":"Spectrum Sensing (SS) comprises the most important component in Cognitive Radio (CR) systems. Cooperative Spectrum Sensing (CSS) is proposed as an effective approach to improve detection performance in fading environments. This paper introduces an efficient energy detection based hard decision CSS algorithm to alleviate the noise uncertainty effect. In the proposed algorithm, the decision threshold is dynamically switched between two levels based on a prior prediction of the Primary User (PU) activity. The two threshold levels are evaluated using an estimated value of the noise uncertainty factor to maximize the probability of detection and minimize the probability of false alarm. The proposed algorithm is studied theoretically to deduce the enhanced detection and false alarm probabilities. Moreover, simulation analysis is used to confirm the theoretical claims and prove the high potency of the proposed scheme compared to the conventional CSS using different fusion rules.","PeriodicalId":227813,"journal":{"name":"2015 Tenth International Conference on Computer Engineering & Systems (ICCES)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132580351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}