Internet of Things (IoT) is characterized by the large volumes of data collection. Since IoT devices are themselves resource-constrained, this data is transferred to cloud-based systems for further processing. This data collected over a period of time possesses high utility as it is useful for multiple analytical, predictive and prescriptive tasks. Therefore, it is crucial that IoT devices transfer the collected data to network gateways before exhausting their storage to prevent loss of data; this issue is referred to as the “data offloading problem”. This paper proposes a technique for fault tolerant offloading of data by IoT devices such that the data collected by them is transferred to the cloud with a minimal loss. The proposed technique employs opportunistic contacts between IoT and mobile fog nodes to provide a fault tolerant enhancement to the IoT architecture. The effectiveness of the proposed method is verified through simulation experiments to assess the reduction in data loss by use of proposed data offloading scheme. It is demonstrated that the method outperforms a state-of-art method.
{"title":"Fault tolerant data offloading in opportunistic fog enhanced IoT architecture","authors":"Parmeet Kaur","doi":"10.3233/mgs-220211","DOIUrl":"https://doi.org/10.3233/mgs-220211","url":null,"abstract":"Internet of Things (IoT) is characterized by the large volumes of data collection. Since IoT devices are themselves resource-constrained, this data is transferred to cloud-based systems for further processing. This data collected over a period of time possesses high utility as it is useful for multiple analytical, predictive and prescriptive tasks. Therefore, it is crucial that IoT devices transfer the collected data to network gateways before exhausting their storage to prevent loss of data; this issue is referred to as the “data offloading problem”. This paper proposes a technique for fault tolerant offloading of data by IoT devices such that the data collected by them is transferred to the cloud with a minimal loss. The proposed technique employs opportunistic contacts between IoT and mobile fog nodes to provide a fault tolerant enhancement to the IoT architecture. The effectiveness of the proposed method is verified through simulation experiments to assess the reduction in data loss by use of proposed data offloading scheme. It is demonstrated that the method outperforms a state-of-art method.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81866023","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}
Djamel Douha, A. Mokhtari, Z. Guessoum, Y. M. Berghout
An agent is an autonomous entity that can perform actions to achieve its goals. It acts in a dynamic environment that may engender failures regarding its behavior. Therefore, a formal testing/verification approach of the agent is required to ensure the correctness of its behavior. In this paper, we propose a Default Logic formalism to abstract an agent behavior as knowledge and reasoning rules, and to verify and test the consistency of the behavior. The considered agents are implemented with JADE framework. Also, agent abstraction is translated into Answer Set Programming and solved by Clingo to generate dynamic and adaptive test cases of the agent behavior. The dynamic test cases allow predicting the agent behavior when a new information arises in the system.
{"title":"Using default logic for agent behavior testing","authors":"Djamel Douha, A. Mokhtari, Z. Guessoum, Y. M. Berghout","doi":"10.3233/mgs-220359","DOIUrl":"https://doi.org/10.3233/mgs-220359","url":null,"abstract":"An agent is an autonomous entity that can perform actions to achieve its goals. It acts in a dynamic environment that may engender failures regarding its behavior. Therefore, a formal testing/verification approach of the agent is required to ensure the correctness of its behavior. In this paper, we propose a Default Logic formalism to abstract an agent behavior as knowledge and reasoning rules, and to verify and test the consistency of the behavior. The considered agents are implemented with JADE framework. Also, agent abstraction is translated into Answer Set Programming and solved by Clingo to generate dynamic and adaptive test cases of the agent behavior. The dynamic test cases allow predicting the agent behavior when a new information arises in the system.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80784999","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}
Nowadays cloud computing has given a new paradigm of computing. Despite several benefits of cloud computing there is still a big challenge of ensuring confidentiality and integrity for sensitive information on the cloud. Therefore to address these challenges without loss of any sensitive information and privacy, we present a novel and robust model called ‘Enhanced Cloud Security using Hyper Elliptic Curve and Biometric’ (ECSHB). The model ECSHB ensures the preservation of data security, privacy, and authentication of data in a cloud environment. The proposed approach combines biometric and hyperelliptic curve cryptography (HECC) techniques to elevate the security of data accessing and resource preservations in the cloud. ECSHB provides a high level of security using less processing power, which will automatically reduce the overall cost. The efficacy of the ECSHB has been evaluated in the form of recognition rate, biometric similarity score, False Matching Ratio (FMR), and False NonMatching Ratio (FNMR). ECSHB has been validated using security threat model analysis in terms of confidentiality. The measure of collision attack, replay attack and non-repudiation is also considered in this work. The evidence of results is compared with some existing work, and the results obtained exhibit better performance in terms of data security and privacy in the cloud environment.
{"title":"A novel model to enhance the data security in cloud environment","authors":"G. Verma, Soumen Kanrar","doi":"10.3233/mgs-220361","DOIUrl":"https://doi.org/10.3233/mgs-220361","url":null,"abstract":"Nowadays cloud computing has given a new paradigm of computing. Despite several benefits of cloud computing there is still a big challenge of ensuring confidentiality and integrity for sensitive information on the cloud. Therefore to address these challenges without loss of any sensitive information and privacy, we present a novel and robust model called ‘Enhanced Cloud Security using Hyper Elliptic Curve and Biometric’ (ECSHB). The model ECSHB ensures the preservation of data security, privacy, and authentication of data in a cloud environment. The proposed approach combines biometric and hyperelliptic curve cryptography (HECC) techniques to elevate the security of data accessing and resource preservations in the cloud. ECSHB provides a high level of security using less processing power, which will automatically reduce the overall cost. The efficacy of the ECSHB has been evaluated in the form of recognition rate, biometric similarity score, False Matching Ratio (FMR), and False NonMatching Ratio (FNMR). ECSHB has been validated using security threat model analysis in terms of confidentiality. The measure of collision attack, replay attack and non-repudiation is also considered in this work. The evidence of results is compared with some existing work, and the results obtained exhibit better performance in terms of data security and privacy in the cloud environment.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87381977","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}
The appliances that are received at a cloud data centre are a compilation of jobs (task) that might be independent or dependent on one another. These tasks are then allocated to diverse virtual machine (VM) in a scheduled way. For this task allocation, various scheduling policies are deployed with the intention of reducing energy utilization and makespan, and increasing cloud resource exploitation as well. A variety of research and studies were done to attain an optimal solution in a single cloud setting, however the similar schemes might not operate on multi-cloud environments. Here, this paper aims to introduce a secured task scheduling model in multi-cloud environment. The developed approach mainly concerns on optimal allocation of tasks via a hybrid optimization theory. Consequently, the developed optimal task allotment considers the objectives like makespan, execution time, security parameters (risk evaluation), utilization cost, maximal service level agreement (SLA) adherence and power usage effectiveness (PUE). For resolving this issue, a novel hybrid algorithm termed as rock hyraxes updated shark smell with logistic mapping (RHU-SLM) is introduced in this work. At last, the superiority of developed approach is proved on varied measures.
{"title":"Multi-objective secure task scheduling based on SLA in multi-cloud environment","authors":"P. Jawade, S. Ramachandram","doi":"10.3233/mgs-220362","DOIUrl":"https://doi.org/10.3233/mgs-220362","url":null,"abstract":"The appliances that are received at a cloud data centre are a compilation of jobs (task) that might be independent or dependent on one another. These tasks are then allocated to diverse virtual machine (VM) in a scheduled way. For this task allocation, various scheduling policies are deployed with the intention of reducing energy utilization and makespan, and increasing cloud resource exploitation as well. A variety of research and studies were done to attain an optimal solution in a single cloud setting, however the similar schemes might not operate on multi-cloud environments. Here, this paper aims to introduce a secured task scheduling model in multi-cloud environment. The developed approach mainly concerns on optimal allocation of tasks via a hybrid optimization theory. Consequently, the developed optimal task allotment considers the objectives like makespan, execution time, security parameters (risk evaluation), utilization cost, maximal service level agreement (SLA) adherence and power usage effectiveness (PUE). For resolving this issue, a novel hybrid algorithm termed as rock hyraxes updated shark smell with logistic mapping (RHU-SLM) is introduced in this work. At last, the superiority of developed approach is proved on varied measures.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79823617","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}
The integration of cognitive radio (CR) in Internet of Things (IoT) is an effective step into the smart technology world. The capability of CR can effectively solve spectrum-related issues for IoT applications, but this association is still a big challenge that has led to a new research dimension of CR-based IoT. To this extend, in this paper the authors propose a novel distributed spectrum management approach based on mobile edge computing (MEC) technology in cooperative environment that enables CRIoT devices to share the unutilized spectrum efficiently. The simulation results show that the proposed solution achieves good performance in terms of spectrum access/sharing and maintains a balance energy consumption of CRIoT users within lower latency.
{"title":"A novel distributed spectrum management in mobile edge computing based cognitive radio Internet of Things networks","authors":"Fatima Zohra Benidriss, Said Limam","doi":"10.3233/mgs-220358","DOIUrl":"https://doi.org/10.3233/mgs-220358","url":null,"abstract":"The integration of cognitive radio (CR) in Internet of Things (IoT) is an effective step into the smart technology world. The capability of CR can effectively solve spectrum-related issues for IoT applications, but this association is still a big challenge that has led to a new research dimension of CR-based IoT. To this extend, in this paper the authors propose a novel distributed spectrum management approach based on mobile edge computing (MEC) technology in cooperative environment that enables CRIoT devices to share the unutilized spectrum efficiently. The simulation results show that the proposed solution achieves good performance in terms of spectrum access/sharing and maintains a balance energy consumption of CRIoT users within lower latency.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82380259","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}
In this paper, we propose a new cloud reactive fault management technique called Hybrid Redundant Array of Independent resources for cloud computing (H_RAIC). The latter uses a new concept called Redundant Array of Independent resources for cloud computing (CRAIR), which is inspired by a powerful conventional technique called Redundant Arrays of Inexpensive Disks (RAID). H_RAIC takes into consideration the cloud resources state and aims to satisfy both cloud users and cloud provider requirements. Our solution was compared with the replication technique which represents a specific case of CRAIR, and with other CRAIR levels defined in this paper. The results show that our technique is a promising solution, that can be used to meet both user and provider requirements.
{"title":"Cloud-oriented fault tolerance technique based on resource state","authors":"Abdelhamid Khiat","doi":"10.3233/mgs-220356","DOIUrl":"https://doi.org/10.3233/mgs-220356","url":null,"abstract":"In this paper, we propose a new cloud reactive fault management technique called Hybrid Redundant Array of Independent resources for cloud computing (H_RAIC). The latter uses a new concept called Redundant Array of Independent resources for cloud computing (CRAIR), which is inspired by a powerful conventional technique called Redundant Arrays of Inexpensive Disks (RAID). H_RAIC takes into consideration the cloud resources state and aims to satisfy both cloud users and cloud provider requirements. Our solution was compared with the replication technique which represents a specific case of CRAIR, and with other CRAIR levels defined in this paper. The results show that our technique is a promising solution, that can be used to meet both user and provider requirements.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90312726","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}
With ever-growing technical advances, performance of complex scientific and engineering applications has arrived at petaflops and exaflops range. However, massive power drawn from the large scale computing infrastructure has caused commensurate rise in electricity consumption, escalating data center ownership costs besides leaving carbon footprints. Judicious scheduling of complex applications with an objective to reduce overall makespan and reduced energy consumption has become one of the biggest confront in the realm of computing architectures. This paper presents a survey on energy efficient scheduling algorithms based on dynamic voltage and frequency scaling (DVFS) and dynamic power management (DPM) techniques. The parameters considered are mainly the makespan, processor energy (dynamic and static) consumption, and network energy (communication) consumption, wherever appropriate during task scheduling.
{"title":"Survey on energy efficient scheduling techniques on cloud computing","authors":"N. Kaur, S. Bansal, R. Bansal","doi":"10.3233/mgs-220357","DOIUrl":"https://doi.org/10.3233/mgs-220357","url":null,"abstract":"With ever-growing technical advances, performance of complex scientific and engineering applications has arrived at petaflops and exaflops range. However, massive power drawn from the large scale computing infrastructure has caused commensurate rise in electricity consumption, escalating data center ownership costs besides leaving carbon footprints. Judicious scheduling of complex applications with an objective to reduce overall makespan and reduced energy consumption has become one of the biggest confront in the realm of computing architectures. This paper presents a survey on energy efficient scheduling algorithms based on dynamic voltage and frequency scaling (DVFS) and dynamic power management (DPM) techniques. The parameters considered are mainly the makespan, processor energy (dynamic and static) consumption, and network energy (communication) consumption, wherever appropriate during task scheduling.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89630023","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}
Software as a Service is evolving as a leader model for cloud service delivery, enabling service providers to remotely deliver hosted, developed and managed software over the Internet. In parallel, some IT services are moving from traditional Internet services to cloud services based on peer-to-peer technologies. However, the P2P-based cloud is a large-scale, heterogeneous and highly dynamic environment whose performance is highly dependent on its ability to maintain persistent availability of SaaS services. In this paper, we propose an approach for improving SaaS service availability in order to meet service quality requirements and maintain performance in a P2P-Based cloud environment. It is mainly based on a new hybrid clustering mechanism that aims to provide a virtual and optimal infrastructure in order to organize the system peers into distinct clusters represented by virtual nodes forming together a virtual layer. This layer allows not only the distribution of peer providers but also the formation of condensed areas of each service of interest for a set of neighboring peers, which improve the availability probability of services in specific regions. In addition, a service availability measurement model was proposed based on the use of the system’s virtual layer taking into account different entities at different levels. The experimental results show that the proposed approach improves the probability of SaaS service availability and the reliability of the P2P-Cloud system. It responds mainly to the large-scale nature of distributed systems as well as making the best trade-off of maintaining QOS in terms of availability, performance and cost.
{"title":"Hybrid fuzzy clustering to improve services availability in P2P-based SaaS-cloud","authors":"A. Achache, Abdelhalim Baaziz, T. Sari","doi":"10.3233/mgs-220355","DOIUrl":"https://doi.org/10.3233/mgs-220355","url":null,"abstract":"Software as a Service is evolving as a leader model for cloud service delivery, enabling service providers to remotely deliver hosted, developed and managed software over the Internet. In parallel, some IT services are moving from traditional Internet services to cloud services based on peer-to-peer technologies. However, the P2P-based cloud is a large-scale, heterogeneous and highly dynamic environment whose performance is highly dependent on its ability to maintain persistent availability of SaaS services. In this paper, we propose an approach for improving SaaS service availability in order to meet service quality requirements and maintain performance in a P2P-Based cloud environment. It is mainly based on a new hybrid clustering mechanism that aims to provide a virtual and optimal infrastructure in order to organize the system peers into distinct clusters represented by virtual nodes forming together a virtual layer. This layer allows not only the distribution of peer providers but also the formation of condensed areas of each service of interest for a set of neighboring peers, which improve the availability probability of services in specific regions. In addition, a service availability measurement model was proposed based on the use of the system’s virtual layer taking into account different entities at different levels. The experimental results show that the proposed approach improves the probability of SaaS service availability and the reliability of the P2P-Cloud system. It responds mainly to the large-scale nature of distributed systems as well as making the best trade-off of maintaining QOS in terms of availability, performance and cost.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91010516","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}
V. MuraliMohan, R. Balajee, Hiren K. Mewada, B. Rajakumar, D. Binu
{"title":"Hybrid machine learning approach based intrusion detection in cloud: A metaheuristic assisted model","authors":"V. MuraliMohan, R. Balajee, Hiren K. Mewada, B. Rajakumar, D. Binu","doi":"10.3233/MGS-220360","DOIUrl":"https://doi.org/10.3233/MGS-220360","url":null,"abstract":"","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70130566","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}
The cloud is an infrastructure that provides decentralized on-demand services. It allows consumers to pay only for the services they use. The consumer is the important entity in the cloud. The violation of the SLA contract between the consumer and the provider often leads to consequences because the service provider has to pay penalties. Data replication is emerging as an ideal solution to meet the new challenges of the cloud. This paper proposes a new replication strategy based on the popularity of data. This strategy adaptively selects the files to be replicated to improve the overall availability of data in the system, minimize query response time, and achieve the required quality of service. In addition, it dynamically determines the number of replicas to add and the best locations to store them. Experimental results show the effectiveness of the proposed strategy.
{"title":"Adaptive replication strategy based on popular content in cloud computing","authors":"Imad Eddine Miloudi, Belabbas Yagoubi, Fatima Zohra Bellounar, Taieb Chachou","doi":"10.3233/mgs-210354","DOIUrl":"https://doi.org/10.3233/mgs-210354","url":null,"abstract":"The cloud is an infrastructure that provides decentralized on-demand services. It allows consumers to pay only for the services they use. The consumer is the important entity in the cloud. The violation of the SLA contract between the consumer and the provider often leads to consequences because the service provider has to pay penalties. Data replication is emerging as an ideal solution to meet the new challenges of the cloud. This paper proposes a new replication strategy based on the popularity of data. This strategy adaptively selects the files to be replicated to improve the overall availability of data in the system, minimize query response time, and achieve the required quality of service. In addition, it dynamically determines the number of replicas to add and the best locations to store them. Experimental results show the effectiveness of the proposed strategy.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78595255","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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