Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921900
V. Berrocal-Plaza, M. A. Vega-Rodríguez, J. M. Sánchez-Pérez
In this paper, we optimize the Reporting Cells Planning Problem in a realistic mobile network. To the best of our knowledge, this is the first work in the literature in which the Reporting Cells Planning Problem is studied in a realistic mobile environment. This problem is based on a mobile location management strategy where the network cells can be in two possible states: Reporting Cells and non-Reporting Cells. In this location management strategy, a mobile station only updates its location when moving to a new Reporting Cell, and it is free to move among non-Reporting Cells without updating its location. The Reporting Cells Planning Problem can be classified as a multiobjective optimization problem with two objective functions: minimize the number of location updates and minimize the number of paging messages. With the aim of finding the best possible set of non-dominated solutions, we have implemented a well-known multiobjective evolutionary algorithm: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Experimental results show that our proposal is able to achieve good sets of non-dominated solutions and, at the same time, to improve the results obtained with other optimization techniques.
{"title":"Studying the Reporting Cells strategy in a realistic mobile environment","authors":"V. Berrocal-Plaza, M. A. Vega-Rodríguez, J. M. Sánchez-Pérez","doi":"10.1109/NaBIC.2014.6921900","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921900","url":null,"abstract":"In this paper, we optimize the Reporting Cells Planning Problem in a realistic mobile network. To the best of our knowledge, this is the first work in the literature in which the Reporting Cells Planning Problem is studied in a realistic mobile environment. This problem is based on a mobile location management strategy where the network cells can be in two possible states: Reporting Cells and non-Reporting Cells. In this location management strategy, a mobile station only updates its location when moving to a new Reporting Cell, and it is free to move among non-Reporting Cells without updating its location. The Reporting Cells Planning Problem can be classified as a multiobjective optimization problem with two objective functions: minimize the number of location updates and minimize the number of paging messages. With the aim of finding the best possible set of non-dominated solutions, we have implemented a well-known multiobjective evolutionary algorithm: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Experimental results show that our proposal is able to achieve good sets of non-dominated solutions and, at the same time, to improve the results obtained with other optimization techniques.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132676538","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}
Pub Date : 2014-10-16DOI: 10.1109/NABIC.2014.6921849
M. Castelli, L. Vanneschi
This paper proposes a hybrid Harmony Search algorithm for the bin-packing problem. The bin-packing problem is a well-known NP-Hard optimization problem. The proposed algorithm (called BPHS) combines a harmony search algorithm, that employs a tournament selection in the generation of new candidate solutions, with a variable neighbourhood search to improve the exploitation ability of the algorithm. The BPHS algorithm has been successfully applied to different instances of the bin-packing problem and it is able to find optimal or near-optimal solutions.
{"title":"A hybrid Harmony search algorithm with variable neighbourhood search for the bin-packing problem","authors":"M. Castelli, L. Vanneschi","doi":"10.1109/NABIC.2014.6921849","DOIUrl":"https://doi.org/10.1109/NABIC.2014.6921849","url":null,"abstract":"This paper proposes a hybrid Harmony Search algorithm for the bin-packing problem. The bin-packing problem is a well-known NP-Hard optimization problem. The proposed algorithm (called BPHS) combines a harmony search algorithm, that employs a tournament selection in the generation of new candidate solutions, with a variable neighbourhood search to improve the exploitation ability of the algorithm. The BPHS algorithm has been successfully applied to different instances of the bin-packing problem and it is able to find optimal or near-optimal solutions.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131647310","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921860
A. Santos, M. Varela, G. Putnik, A. Madureira
Extended Manufacturing Environments (EMEs) are nowadays growing due to the increase on Distributed and Virtual Enterprises, which led to an emergent need to apply scheduling approaches accordingly. This can be achieved in several different ways, namely by putting forward new approaches or by trying to adapt existing ones. In this paper the adaptation of some existing scheduling methods is proposed for solving a two stage manufacturing scheduling problem, and an illustrative example is presented. Several approaches were analyses, namely through the use of the ANOVA and the Post Hoc Scheffe's test, that demonstrated the superior performance of one of the proposed methods.
如今，由于分布式和虚拟企业的增加，扩展制造环境（EMEs）也在不断发展，这就迫切需要相应的调度方法。这可以通过几种不同的方式来实现，即提出新方法或尝试调整现有方法。本文提出了一些现有调度方法的调整方案，用于解决两阶段生产调度问题，并给出了一个示例。分析了几种方法，即通过使用方差分析和Post Hoc Scheffe's检验，证明了其中一种建议方法的优越性能。
{"title":"Alternative approaches analysis for scheduling in an Extended Manufacturing Environment","authors":"A. Santos, M. Varela, G. Putnik, A. Madureira","doi":"10.1109/NaBIC.2014.6921860","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921860","url":null,"abstract":"Extended Manufacturing Environments (EMEs) are nowadays growing due to the increase on Distributed and Virtual Enterprises, which led to an emergent need to apply scheduling approaches accordingly. This can be achieved in several different ways, namely by putting forward new approaches or by trying to adapt existing ones. In this paper the adaptation of some existing scheduling methods is proposed for solving a two stage manufacturing scheduling problem, and an illustrative example is presented. Several approaches were analyses, namely through the use of the ANOVA and the Post Hoc Scheffe's test, that demonstrated the superior performance of one of the proposed methods.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129185284","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921873
Filipa de Oliveira Teixeira, Lara Oliveira, L. Varela
This study aims to determinate which scheduling rule should be applied, for minimizing the makespan value, and maximizing the utilization level of a production system, which includes a set of three parallel processors, each one integrating five machines, by using a simulation approach based on Arena. A first simulation was done under random conditions, not attending to any kind of rule, and after some dispatching rules were applied, namely the shortest queue rule; the shortest processing time rule; the longest processing time rule; and combination of rules through a weighted sum about completion times and the work in process. A comparative analysis about the application of these rules is carried out in this paper. The rules that have been applied to achieve the goals were selected taking into account not only the problem to be studied, but also different conditions present in a real production system environment. The problem consists on a complex and dynamic system, where each job has the same priority and different processing times, without preemption.
{"title":"Comparative analysis of scheduling rules through arena for parallel machines","authors":"Filipa de Oliveira Teixeira, Lara Oliveira, L. Varela","doi":"10.1109/NaBIC.2014.6921873","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921873","url":null,"abstract":"This study aims to determinate which scheduling rule should be applied, for minimizing the makespan value, and maximizing the utilization level of a production system, which includes a set of three parallel processors, each one integrating five machines, by using a simulation approach based on Arena. A first simulation was done under random conditions, not attending to any kind of rule, and after some dispatching rules were applied, namely the shortest queue rule; the shortest processing time rule; the longest processing time rule; and combination of rules through a weighted sum about completion times and the work in process. A comparative analysis about the application of these rules is carried out in this paper. The rules that have been applied to achieve the goals were selected taking into account not only the problem to be studied, but also different conditions present in a real production system environment. The problem consists on a complex and dynamic system, where each job has the same priority and different processing times, without preemption.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133117662","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921870
R. Kamimura
In this paper, we propose a new type of supervised multi-layered self-organizing map and examine to what extent information content in multi-layered networks can be increased. We have so far introduced the information-theoretic SOM in a single layer for increasing information content. However, we have found some cases where information content cannot be increased by single-layer networks. We used the multi-layered network and we found that mutual information tended to increase even for higher layers. The corresponding U-matrices showed clearer class structure even for higher layers. Then, we applied the method to the improvement of prediction performance. The prediction performance could be improved when the number of layers was appropriately chosen.
{"title":"Information acquisition performance by supervised information-theoretic self-organizing maps","authors":"R. Kamimura","doi":"10.1109/NaBIC.2014.6921870","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921870","url":null,"abstract":"In this paper, we propose a new type of supervised multi-layered self-organizing map and examine to what extent information content in multi-layered networks can be increased. We have so far introduced the information-theoretic SOM in a single layer for increasing information content. However, we have found some cases where information content cannot be increased by single-layer networks. We used the multi-layered network and we found that mutual information tended to increase even for higher layers. The corresponding U-matrices showed clearer class structure even for higher layers. Then, we applied the method to the improvement of prediction performance. The prediction performance could be improved when the number of layers was appropriately chosen.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124946132","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921865
María Arsuaga-Ríos, M. A. Vega-Rodríguez
Green Computing also known as Green IT is becoming a hot topic in the computational field during these last years. Green Computing consists of enabling organizations to make a more rational and efficient use of their technological resources and reduce costs while adopting technologies and working methods more respectful of the environment. Execution time and energy consumption are also conflicting objectives, because faster resources frequently imply higher energy consumptions. In this paper, we optimize both: execution time and energy consumption to resolve the task scheduling problem in Grid environments. MOABC is a swarm algorithm inspired in the bees behaviour and it is compared with MO-FA which is other swarm algorithm inspired in the fireflies behaviour. These algorithms are also compared with the well-known NSGA-II to evaluate their multiobjective properties. Moreover, the best algorithm, MOABC, is compared with MOHEFT, the most popular algorithm for workflow scheduling and with two real grid schedulers as WMS or DBC. The results obtained point out MOABC as the best approach in all the cases studied.
{"title":"Energy optimization for task scheduling in distributed systems by an Artificial Bee Colony approach","authors":"María Arsuaga-Ríos, M. A. Vega-Rodríguez","doi":"10.1109/NaBIC.2014.6921865","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921865","url":null,"abstract":"Green Computing also known as Green IT is becoming a hot topic in the computational field during these last years. Green Computing consists of enabling organizations to make a more rational and efficient use of their technological resources and reduce costs while adopting technologies and working methods more respectful of the environment. Execution time and energy consumption are also conflicting objectives, because faster resources frequently imply higher energy consumptions. In this paper, we optimize both: execution time and energy consumption to resolve the task scheduling problem in Grid environments. MOABC is a swarm algorithm inspired in the bees behaviour and it is compared with MO-FA which is other swarm algorithm inspired in the fireflies behaviour. These algorithms are also compared with the well-known NSGA-II to evaluate their multiobjective properties. Moreover, the best algorithm, MOABC, is compared with MOHEFT, the most popular algorithm for workflow scheduling and with two real grid schedulers as WMS or DBC. The results obtained point out MOABC as the best approach in all the cases studied.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115288959","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921852
Xiaoqian Zhang, Bo Yang, Lin Wang, Zhifeng Liang, A. Abraham
Floating Centroids Method (FCM) is a new method to improve the performance of neural network classifier. But the K-Means clustering algorithm used in FCM is sensitive to outliers. So this weakness will influence the performance of classifier to a certain extent. In this paper, K-Medoids clustering algorithm which can diminish the sensitivity to the outliers is used to partition the mapping points into some disjoint subsets to improve FCM's robustness and performance. Some data sets from UCI Machine Learning Repository are employed in our experiments. The results show a better performance for the FCM using our improved method.
{"title":"Improvement of FCM neural network classifier using K-Medoids clustering","authors":"Xiaoqian Zhang, Bo Yang, Lin Wang, Zhifeng Liang, A. Abraham","doi":"10.1109/NaBIC.2014.6921852","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921852","url":null,"abstract":"Floating Centroids Method (FCM) is a new method to improve the performance of neural network classifier. But the K-Means clustering algorithm used in FCM is sensitive to outliers. So this weakness will influence the performance of classifier to a certain extent. In this paper, K-Medoids clustering algorithm which can diminish the sensitivity to the outliers is used to partition the mapping points into some disjoint subsets to improve FCM's robustness and performance. Some data sets from UCI Machine Learning Repository are employed in our experiments. The results show a better performance for the FCM using our improved method.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126866287","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921856
A. Santos, A. Madureira, M. Varela
In the current global market organizations face uncertainties and shorter response time. In order to remain competitive many organizations adopted flexible resources capable of performing several operations with different performance capabilities. The unrelated parallel-machines makespan minimization problem (Rm∥Cmax) is known to be NP-hard or too complex to be solved exactly. Among the several heuristics used for solving this problem, it is possible to identify MCT (Minimum Completion Time) that allocates tasks in a random order to the minimum completion time machine. This paper proposes an ordered approach to the MCT heuristic. MOMCT (Modified Ordered Minimum Completion Time), which will order tasks in accordance to the mean difference of the completion time on each machine and the minimum completion time machine. The computational study demonstrated the improved performance of the proposed ordered approach to the MCT heuristic.
{"title":"An ordered approach to Minimum Completion Time in unrelated parallel-machines for the makespan optimization","authors":"A. Santos, A. Madureira, M. Varela","doi":"10.1109/NaBIC.2014.6921856","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921856","url":null,"abstract":"In the current global market organizations face uncertainties and shorter response time. In order to remain competitive many organizations adopted flexible resources capable of performing several operations with different performance capabilities. The unrelated parallel-machines makespan minimization problem (Rm∥Cmax) is known to be NP-hard or too complex to be solved exactly. Among the several heuristics used for solving this problem, it is possible to identify MCT (Minimum Completion Time) that allocates tasks in a random order to the minimum completion time machine. This paper proposes an ordered approach to the MCT heuristic. MOMCT (Modified Ordered Minimum Completion Time), which will order tasks in accordance to the mean difference of the completion time on each machine and the minimum completion time machine. The computational study demonstrated the improved performance of the proposed ordered approach to the MCT heuristic.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131450493","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921885
Gopinath Chennupati, Jeannie Fitzgerald, C. Ryan
In this paper we investigate a novel technique that optimizes the execution time of Grammatical Evolution through the usage of on-chip multiple processors. This technique, Multicore Grammatical Evolution (MCGE) evolves natively parallel programs with the help of OpenMP primitives through the grammars, such that not only can we exploit parallelism while evolving individuals, but the final individuals produced can also be executed on parallel architectures even outside the evolutionary system. We test MCGE on two difficult benchmark GP problems and show its efficiency in exploiting the power of the multicore architectures. We further discuss that, on these problems, the system evolves longer individuals while they are evaluated quicker than their serial implementation.
{"title":"On the efficiency of Multi-core Grammatical Evolution (MCGE) evolving multi-core parallel programs","authors":"Gopinath Chennupati, Jeannie Fitzgerald, C. Ryan","doi":"10.1109/NaBIC.2014.6921885","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921885","url":null,"abstract":"In this paper we investigate a novel technique that optimizes the execution time of Grammatical Evolution through the usage of on-chip multiple processors. This technique, Multicore Grammatical Evolution (MCGE) evolves natively parallel programs with the help of OpenMP primitives through the grammars, such that not only can we exploit parallelism while evolving individuals, but the final individuals produced can also be executed on parallel architectures even outside the evolutionary system. We test MCGE on two difficult benchmark GP problems and show its efficiency in exploiting the power of the multicore architectures. We further discuss that, on these problems, the system evolves longer individuals while they are evaluated quicker than their serial implementation.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114352375","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}
Pub Date : 2014-10-16DOI: 10.1109/NaBIC.2014.6921886
P. Gonçalves, F. Santos, P. M. B. Torres
Intelligent Robots can take advantage of a distributed, web-based information system deployed in the cloud to perform high level tasks. This paper proposes a robotic control framework suited to be used by low-cost robots, performing teloperated and/or autonomous tasks. The first part is dedicated to the development of an Android based robot control framework. This framework connects to specific low-level controllers that were developed for multicopters, wheeled/tracked mobile robots. The second part is dedicated to “place” the Android based robot in the cloud. There, the robot can perform Cloud based highly automated cognitive tasks in order to optimize their use and take best advantage of previous knowledge models, e.g., objects databases or 3D world models. Also, the robot can be controlled remotely using a classical teleoperation mode, using wifi networks. First experiments are presented when a tracked robot is performing surveillance tasks, while its state can be changed to teleoperation/videoconferencing mode, while interacting with a reasoning engine in the Cloud.
{"title":"Towards a low-cost framework for Intelligent Robots","authors":"P. Gonçalves, F. Santos, P. M. B. Torres","doi":"10.1109/NaBIC.2014.6921886","DOIUrl":"https://doi.org/10.1109/NaBIC.2014.6921886","url":null,"abstract":"Intelligent Robots can take advantage of a distributed, web-based information system deployed in the cloud to perform high level tasks. This paper proposes a robotic control framework suited to be used by low-cost robots, performing teloperated and/or autonomous tasks. The first part is dedicated to the development of an Android based robot control framework. This framework connects to specific low-level controllers that were developed for multicopters, wheeled/tracked mobile robots. The second part is dedicated to “place” the Android based robot in the cloud. There, the robot can perform Cloud based highly automated cognitive tasks in order to optimize their use and take best advantage of previous knowledge models, e.g., objects databases or 3D world models. Also, the robot can be controlled remotely using a classical teleoperation mode, using wifi networks. First experiments are presented when a tracked robot is performing surveillance tasks, while its state can be changed to teleoperation/videoconferencing mode, while interacting with a reasoning engine in the Cloud.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132279457","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}
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