Pub Date : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285936
Beomsu Kim, Ki-Il Kim
IEEE 802.15.6, which is the standard for wireless body area networks (WBANs), defines a unique link allocation interval called the managed access phase to meet the QoS requirements of medical applications. The hub grants an uplink allocation interval to the node according to predetermined scheduling policies; however, the IEEE 802.15.6 standard does not consider user priorities in the uplink scheduling. To address this problem, many priority-based link scheduling algorithms have been proposed; however, these algorithms ignore the unique characteristics of WBANs, such as changes in body posture and damage to body tissue, thereby leading to a waste of resources. To overcome these limitations, in this study, we propose three scheduling parameters that are suitable for WBANs, and logically determine the relationship between the proposed parameters using the multi-criteria decision making (MCDM) method. Furthermore, a priority-based dynamic link scheduling algorithm is proposed, which is based on the results of the MCDM. The simulation results prove that our proposed approach can balance the resource allocation, while maintaining the performance of high-priority nodes in terms of throughput, delay, and power consumption.
{"title":"A Priority-based Dynamic Link Scheduling Algorithm Using Multi-criteria Decision Making in Wireless Body Area Networks","authors":"Beomsu Kim, Ki-Il Kim","doi":"10.1109/MASCOTS50786.2020.9285936","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285936","url":null,"abstract":"IEEE 802.15.6, which is the standard for wireless body area networks (WBANs), defines a unique link allocation interval called the managed access phase to meet the QoS requirements of medical applications. The hub grants an uplink allocation interval to the node according to predetermined scheduling policies; however, the IEEE 802.15.6 standard does not consider user priorities in the uplink scheduling. To address this problem, many priority-based link scheduling algorithms have been proposed; however, these algorithms ignore the unique characteristics of WBANs, such as changes in body posture and damage to body tissue, thereby leading to a waste of resources. To overcome these limitations, in this study, we propose three scheduling parameters that are suitable for WBANs, and logically determine the relationship between the proposed parameters using the multi-criteria decision making (MCDM) method. Furthermore, a priority-based dynamic link scheduling algorithm is proposed, which is based on the results of the MCDM. The simulation results prove that our proposed approach can balance the resource allocation, while maintaining the performance of high-priority nodes in terms of throughput, delay, and power consumption.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129810114","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285947
Emilio Incerto, Annalisa Napolitano, M. Tribastone
Markov chains are a useful model for the quantitative analysis of extra-functional properties of software systems such as performance, reliability, and energy consumption. However building Markov models of software systems remains a difficult task. Here we present a statistical method that learns a Markov chain directly from a program, by means of execution runs with inputs sampled by given probability distributions. Our technique is based on learning algorithms for so-called variable length Markov chains, which allow us to capture data dependency throughout execution paths by encoding part of the program history into each state of the chain. Our domain-specific adaptation exploits structural information about the program through its control-flow graph. Using a prototype implementation, we show that this approach represents a significant improvement over state-of-the-art general-purpose learning algorithms, providing accurate models in a number of benchmark programs.
{"title":"Statistical Learning of Markov Chains of Programs","authors":"Emilio Incerto, Annalisa Napolitano, M. Tribastone","doi":"10.1109/MASCOTS50786.2020.9285947","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285947","url":null,"abstract":"Markov chains are a useful model for the quantitative analysis of extra-functional properties of software systems such as performance, reliability, and energy consumption. However building Markov models of software systems remains a difficult task. Here we present a statistical method that learns a Markov chain directly from a program, by means of execution runs with inputs sampled by given probability distributions. Our technique is based on learning algorithms for so-called variable length Markov chains, which allow us to capture data dependency throughout execution paths by encoding part of the program history into each state of the chain. Our domain-specific adaptation exploits structural information about the program through its control-flow graph. Using a prototype implementation, we show that this approach represents a significant improvement over state-of-the-art general-purpose learning algorithms, providing accurate models in a number of benchmark programs.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134390561","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285957
F. Aleskerov, Alina Roman, Anna Rezyapova, V. Yakuba
New centrality indices in networks are introduced in which parameters of a node and a group influence of nodes to a node are taken into account. The Bundle Influence and Pivotal Influence as well as Copeland in-degree indices are evaluated using the data on international trade and international migration. The influence of the countries is evaluated for four years, 2001, 2006, 2011, and 2016. The Total Influence as a linear combination of the three indices is calculated.
{"title":"New Centrality Measures in Networks and their Applications to the International Trade and Migration Networks","authors":"F. Aleskerov, Alina Roman, Anna Rezyapova, V. Yakuba","doi":"10.1109/MASCOTS50786.2020.9285957","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285957","url":null,"abstract":"New centrality indices in networks are introduced in which parameters of a node and a group influence of nodes to a node are taken into account. The Bundle Influence and Pivotal Influence as well as Copeland in-degree indices are evaluated using the data on international trade and international migration. The influence of the countries is evaluated for four years, 2001, 2006, 2011, and 2016. The Total Influence as a linear combination of the three indices is calculated.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134437300","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285940
Renato L. F. Cunha, L. Chaimowicz
We propose a way to model and integrate HPC scheduling simulators into a popular Reinforcement Learning toolkit. We show experimentally that such an approach not only aids researchers being able to iterate faster by means of software reuse, but also to achieve state-of-the-art performance with 10x less interactions with the environment. We validate the simulation model's correctness by using unit tests, assertions and experimental comparisons. We also share an open source implementation of the model that will benefit researchers in resource management tasks assisted by Machine Learning.
{"title":"Towards a common environment for learning scheduling algorithms","authors":"Renato L. F. Cunha, L. Chaimowicz","doi":"10.1109/MASCOTS50786.2020.9285940","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285940","url":null,"abstract":"We propose a way to model and integrate HPC scheduling simulators into a popular Reinforcement Learning toolkit. We show experimentally that such an approach not only aids researchers being able to iterate faster by means of software reuse, but also to achieve state-of-the-art performance with 10x less interactions with the environment. We validate the simulation model's correctness by using unit tests, assertions and experimental comparisons. We also share an open source implementation of the model that will benefit researchers in resource management tasks assisted by Machine Learning.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125669590","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285935
2020 IEEE 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.
2020 IEEE第28届计算机和电信系统建模、分析和仿真国际研讨会。
{"title":"2020 IEEE 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems","authors":"","doi":"10.1109/MASCOTS50786.2020.9285935","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285935","url":null,"abstract":"2020 IEEE 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115537419","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285934
Mulugeta Ayalew Tamiru, G. Pierre, Johan Tordsson, E. Elmroth
As resources in geo-distributed environments are typically located in remote sites characterized by high latency and intermittent network connectivity, delays and transient network failures are common between the management layer and the remote resources. In this paper, we show that delays and transient network failures coupled with static configuration, including the default configuration parameter values, can lead to instability of application deployments in Kubernetes Federation, making applications unavailable for long periods of time. Leveraging on the benefits of configuration tuning, we propose a feedback controller to dynamically adjust the concerned configuration parameter to improve the stability of application deployments without slowing down the detection of hard failures. We show the effectiveness of our approach in a geo-distributed setup across five sites of Grid'5000, bringing system stability from 83-92% with no controller to 99.5-100% using the controller.
{"title":"Instability in Geo-Distributed Kubernetes Federation: Causes and Mitigation","authors":"Mulugeta Ayalew Tamiru, G. Pierre, Johan Tordsson, E. Elmroth","doi":"10.1109/MASCOTS50786.2020.9285934","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285934","url":null,"abstract":"As resources in geo-distributed environments are typically located in remote sites characterized by high latency and intermittent network connectivity, delays and transient network failures are common between the management layer and the remote resources. In this paper, we show that delays and transient network failures coupled with static configuration, including the default configuration parameter values, can lead to instability of application deployments in Kubernetes Federation, making applications unavailable for long periods of time. Leveraging on the benefits of configuration tuning, we propose a feedback controller to dynamically adjust the concerned configuration parameter to improve the stability of application deployments without slowing down the detection of hard failures. We show the effectiveness of our approach in a geo-distributed setup across five sites of Grid'5000, bringing system stability from 83-92% with no controller to 99.5-100% using the controller.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131371261","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285959
E. Gelenbe, Pawel Boryszko, Miltiadis G. Siavvas, J. Domańska
We study programs which operate in the presence of possible failures and which must be restarted from the beginning after each failure. In such systems checkpointsare introduced to reduce the large costs of program restarts when failures occur. Here we suggest that checkpoints should be introduced in a manner which assures effective reliability, while reducing both the computational overhead as much as possible, but also to save energy. We compute the total average program execution time in the presence of checkoints so as to limit the re-execution time of the program from the most recent checkpoint. We also study the total energy cnsumption of the program under the same conditions, and formulate an optimization problem to minimize a wighted sum of both average computation time and energy. This approach is placed in the context of Application Level Checkpointing and Restart (ALCR). We then focus on checkpoints placed at the beginning of a loop, and derive the optimum placement of checkpoints to minimize a weighted combination of the program's execution time and energy consumption. Numerical results are presented to illustrate the analysis. Finally we describe a software tool with a graphical interface that has been designed to assist a system designer in choosing the optimum checkpoint for a given program as a function of different failure rates and other parameters.
{"title":"Optimum Checkpoints for Time and Energy","authors":"E. Gelenbe, Pawel Boryszko, Miltiadis G. Siavvas, J. Domańska","doi":"10.1109/MASCOTS50786.2020.9285959","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285959","url":null,"abstract":"We study programs which operate in the presence of possible failures and which must be restarted from the beginning after each failure. In such systems checkpointsare introduced to reduce the large costs of program restarts when failures occur. Here we suggest that checkpoints should be introduced in a manner which assures effective reliability, while reducing both the computational overhead as much as possible, but also to save energy. We compute the total average program execution time in the presence of checkoints so as to limit the re-execution time of the program from the most recent checkpoint. We also study the total energy cnsumption of the program under the same conditions, and formulate an optimization problem to minimize a wighted sum of both average computation time and energy. This approach is placed in the context of Application Level Checkpointing and Restart (ALCR). We then focus on checkpoints placed at the beginning of a loop, and derive the optimum placement of checkpoints to minimize a weighted combination of the program's execution time and energy consumption. Numerical results are presented to illustrate the analysis. Finally we describe a software tool with a graphical interface that has been designed to assist a system designer in choosing the optimum checkpoint for a given program as a function of different failure rates and other parameters.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129935464","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285933
Malek Musleh, Roberto Peñaranda, Allister Alemania, P. Yébenes, Gene Y. Wu, Jan Zielinski, K. Raszkowski, N. Ni, Scott Diesing, Anupama Kurpad, R. Huggahalli, Curt E. Bruns, Steven Miller, Sujoy Sen
The explosive growth in cloud-computing and overall data center system growth has created an unprecedented demand on system architects and designers to continuously develop more complex system networks to effectively satisfy the insatiable appetite to process, move, and store large amounts of data. Nonlinear system behavior caused by emerging workloads and use-cases, varying end-to-end congestion protocols, and heterogeneity in the various compute and storage capabilities of custom designed accelerators further compounds the design problem. Modern simulation methodologies lack a cohesive and efficient framework to address the interoperability of the intersecting layers at scale. In this paper, we present a simulation framework for evaluating congestion control protocols. Furthermore, we present a set of optimizations that enable analysis for longer simulated times and at network scales up to 128K nodes, which is vital for proper analysis of workloads that require long run times (e.g., AI training) or workloads that are known to have scaling issues (e.g., RDMA). Specifically, we evaluate congestion control performance at various scales, study the implications of topology scaling on congestion, and the performance impact of simultaneous heterogeneous protocols.
{"title":"Fabsim-X: A Simulation Framework for the Analysis of Large-Scale Topologies and Congestion Control Protocols in Data Center Networks","authors":"Malek Musleh, Roberto Peñaranda, Allister Alemania, P. Yébenes, Gene Y. Wu, Jan Zielinski, K. Raszkowski, N. Ni, Scott Diesing, Anupama Kurpad, R. Huggahalli, Curt E. Bruns, Steven Miller, Sujoy Sen","doi":"10.1109/MASCOTS50786.2020.9285933","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285933","url":null,"abstract":"The explosive growth in cloud-computing and overall data center system growth has created an unprecedented demand on system architects and designers to continuously develop more complex system networks to effectively satisfy the insatiable appetite to process, move, and store large amounts of data. Nonlinear system behavior caused by emerging workloads and use-cases, varying end-to-end congestion protocols, and heterogeneity in the various compute and storage capabilities of custom designed accelerators further compounds the design problem. Modern simulation methodologies lack a cohesive and efficient framework to address the interoperability of the intersecting layers at scale. In this paper, we present a simulation framework for evaluating congestion control protocols. Furthermore, we present a set of optimizations that enable analysis for longer simulated times and at network scales up to 128K nodes, which is vital for proper analysis of workloads that require long run times (e.g., AI training) or workloads that are known to have scaling issues (e.g., RDMA). Specifically, we evaluate congestion control performance at various scales, study the implications of topology scaling on congestion, and the performance impact of simultaneous heterogeneous protocols.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134287240","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285961
Huibo Bi, E. Gelenbe, Yanyan Chen
Although the abilities of human beings as participants in urban traffic, when they take decisions and interact with the transportation infrastructure and other vehicles, have been greatly amplified by powerful portable devices and efficient human-machine interfaces, the intelligence of vehicle drivers and pedestrians and their possible pro-social behaviour such as helpfulness and sense of duty, have been excluded in previous studies of Intelligent Transportation Systems (ITS). Thus the robustness of an ITS has not been evaluated as a function of the likelihood that participants follow instructions. Moreover, much effort has been dedicated to the use of Artificial Intelligence, while in fact many tasks can be easily accomplished by road users in the system who use ordinary human intelligence. Hence, in this paper, we propose a reward mechanism to integrate the intelligence of human road users into a large-scale transportation system to improve the effectiveness and robustness of the system by introducing a transportation-related task publishing system which is assisted by a queueing network model. The experimental results show that the use of a reward mechanism can significantly improve the performance of the transportation system in terms of average travel time of vehicles and the average response time to various tasks.
{"title":"Incentive mechanism for collective coordination in an urban intelligent transportation system using G-networks","authors":"Huibo Bi, E. Gelenbe, Yanyan Chen","doi":"10.1109/MASCOTS50786.2020.9285961","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285961","url":null,"abstract":"Although the abilities of human beings as participants in urban traffic, when they take decisions and interact with the transportation infrastructure and other vehicles, have been greatly amplified by powerful portable devices and efficient human-machine interfaces, the intelligence of vehicle drivers and pedestrians and their possible pro-social behaviour such as helpfulness and sense of duty, have been excluded in previous studies of Intelligent Transportation Systems (ITS). Thus the robustness of an ITS has not been evaluated as a function of the likelihood that participants follow instructions. Moreover, much effort has been dedicated to the use of Artificial Intelligence, while in fact many tasks can be easily accomplished by road users in the system who use ordinary human intelligence. Hence, in this paper, we propose a reward mechanism to integrate the intelligence of human road users into a large-scale transportation system to improve the effectiveness and robustness of the system by introducing a transportation-related task publishing system which is assisted by a queueing network model. The experimental results show that the use of a reward mechanism can significantly improve the performance of the transportation system in terms of average travel time of vehicles and the average response time to various tasks.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131090097","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 : 2020-11-17DOI: 10.1109/MASCOTS50786.2020.9285965
Youssef Ait El Mahjoub, J. Fourneau, Hind Castel-Taleb
We consider an Energy Packet Network (EPN) model where the service times of the packets follow a Coxian distribution. EPNs are a recent type of models proposed by Gelenbe and his colleagues to study the interactions between energy consumption and the processing or the transmission of data. We prove that such a network has a product form solution for its steady-state distribution. We also state some sufficient conditions for the existence of the flow equations. Finally we study the performances and the energy consumption and we show how to optimize the assignemenl of Δ solar panels over a sensor network.
{"title":"Energy Packet Networks with general service time distribution","authors":"Youssef Ait El Mahjoub, J. Fourneau, Hind Castel-Taleb","doi":"10.1109/MASCOTS50786.2020.9285965","DOIUrl":"https://doi.org/10.1109/MASCOTS50786.2020.9285965","url":null,"abstract":"We consider an Energy Packet Network (EPN) model where the service times of the packets follow a Coxian distribution. EPNs are a recent type of models proposed by Gelenbe and his colleagues to study the interactions between energy consumption and the processing or the transmission of data. We prove that such a network has a product form solution for its steady-state distribution. We also state some sufficient conditions for the existence of the flow equations. Finally we study the performances and the energy consumption and we show how to optimize the assignemenl of Δ solar panels over a sensor network.","PeriodicalId":272614,"journal":{"name":"2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117095835","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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