Pub Date : 2020-05-01DOI: 10.1109/WOCC48579.2020.9114942
Tiantian Yang, Rong Chai, Liping Zhang
Mobile edge computing (MEC) has been recognized as a promising technique which provides mobile devices (MDs) with enhanced computation capability. In this paper, we consider a multi-user, multi-server MEC system which consists of a number of MDs and multiple base stations (BSs) deployed with MEC servers. We assume that computation tasks can be executed locally at the MDs or be offloaded to the MEC servers. Further assume that each MEC server may execute computation tasks for multiple MDs, however, the tasks sharing one MEC server should be scheduled sequentially. We jointly study computation task offloading and scheduling scheme for the MDs and formulate the problem of joint task offloading and scheduling as a task execution latency minimization problem. Since the optimization problem is a mixed integer nonlinear problem which cannot be solved using conventional methods, we transform it into two subproblems, i.e., task partition subproblem and task scheduling subproblem. Under the assumption that task scheduling strategy is given, task partition subproblem is a set of single variable optimization problems, which can be solved easily. To tackle the task scheduling subproblem, we propose a heuristic algorithm, which first determines complete local computing mode for the MDs, then calculates local optimal strategy for the MDs. In the case that multiple MDs may share one MEC server, various priorities are then assigned to the MDs and corresponding computing mode and task scheduling strategy are determined for the MDs with different priorities. Numerical results demonstrate the effectiveness of the proposed scheme.
{"title":"Latency Optimization-based Joint Task Offloading and Scheduling for Multi-user MEC System","authors":"Tiantian Yang, Rong Chai, Liping Zhang","doi":"10.1109/WOCC48579.2020.9114942","DOIUrl":"https://doi.org/10.1109/WOCC48579.2020.9114942","url":null,"abstract":"Mobile edge computing (MEC) has been recognized as a promising technique which provides mobile devices (MDs) with enhanced computation capability. In this paper, we consider a multi-user, multi-server MEC system which consists of a number of MDs and multiple base stations (BSs) deployed with MEC servers. We assume that computation tasks can be executed locally at the MDs or be offloaded to the MEC servers. Further assume that each MEC server may execute computation tasks for multiple MDs, however, the tasks sharing one MEC server should be scheduled sequentially. We jointly study computation task offloading and scheduling scheme for the MDs and formulate the problem of joint task offloading and scheduling as a task execution latency minimization problem. Since the optimization problem is a mixed integer nonlinear problem which cannot be solved using conventional methods, we transform it into two subproblems, i.e., task partition subproblem and task scheduling subproblem. Under the assumption that task scheduling strategy is given, task partition subproblem is a set of single variable optimization problems, which can be solved easily. To tackle the task scheduling subproblem, we propose a heuristic algorithm, which first determines complete local computing mode for the MDs, then calculates local optimal strategy for the MDs. In the case that multiple MDs may share one MEC server, various priorities are then assigned to the MDs and corresponding computing mode and task scheduling strategy are determined for the MDs with different priorities. Numerical results demonstrate the effectiveness of the proposed scheme.","PeriodicalId":187607,"journal":{"name":"2020 29th Wireless and Optical Communications Conference (WOCC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133552699","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 : 2020-05-01DOI: 10.1109/WOCC48579.2020.9114932
S. Baidya, R. Hewett
Software Defined Networking (SDN) is an emerging technology that has increasingly become popular for implementing modern infrastructures. SDN offers advantages of programmable and flexible network management over the traditional practice. As more and more SDN-based networks are being implemented, it is necessary to consider security issues especially those that are inherent from SDN. This paper addresses an important SDN specific security issue, namely a host location (tracking) attack, where an attacker compromises a host and captures its location information to manipulate the packets and trick the controller. Such an attack can potentially lead to many harmful effects including disruption of network traffic and denial of services. In particular, we introduce a new host location attack that exploits unused ports, along with its countermeasure for the controller to detect and take appropriate actions. We illustrate and evaluate the proposed detection mechanism by network simulations. The results obtained from our experiments are effective and promising.
{"title":"Detecting host location attacks in SDN-based networks","authors":"S. Baidya, R. Hewett","doi":"10.1109/WOCC48579.2020.9114932","DOIUrl":"https://doi.org/10.1109/WOCC48579.2020.9114932","url":null,"abstract":"Software Defined Networking (SDN) is an emerging technology that has increasingly become popular for implementing modern infrastructures. SDN offers advantages of programmable and flexible network management over the traditional practice. As more and more SDN-based networks are being implemented, it is necessary to consider security issues especially those that are inherent from SDN. This paper addresses an important SDN specific security issue, namely a host location (tracking) attack, where an attacker compromises a host and captures its location information to manipulate the packets and trick the controller. Such an attack can potentially lead to many harmful effects including disruption of network traffic and denial of services. In particular, we introduce a new host location attack that exploits unused ports, along with its countermeasure for the controller to detect and take appropriate actions. We illustrate and evaluate the proposed detection mechanism by network simulations. The results obtained from our experiments are effective and promising.","PeriodicalId":187607,"journal":{"name":"2020 29th Wireless and Optical Communications Conference (WOCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127708161","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 : 2020-05-01DOI: 10.1109/WOCC48579.2020.9114922
N. Ceccarelli, Paulo Alexandre Regis, S. Sengupta, David Feil-Seifer
Efficient arrangement of UAVs in a swarm formation is essential to the functioning of the swarm as a temporary communication network. Such a network could assist in search and rescue efforts by providing first responders with a means of communication. We propose a user-friendly and effective system for calculating and visualizing an optimal layout of UAVs. An initial calculation to gather parameter information is followed by the proposed algorithm that generates an optimal solution. A visualization is displayed in an easy-to-comprehend manner after the proposed iterative genetic algorithm finds an optimal solution. The proposed system runs iteratively, adding UAV at each intermediate conclusion, until a solution is found. Information is passed between runs of the iterative genetic algorithm to reduce runtime and complexity. The results from testing show that the proposed algorithm yields optimal solutions more frequently than the k-means clustering algorithm. This system finds an optimal solution 80% of the time while k-means clustering is unable to find a solution when presented with a complex problem.
{"title":"Optimal UAV Positioning for a Temporary Network Using an Iterative Genetic Algorithm","authors":"N. Ceccarelli, Paulo Alexandre Regis, S. Sengupta, David Feil-Seifer","doi":"10.1109/WOCC48579.2020.9114922","DOIUrl":"https://doi.org/10.1109/WOCC48579.2020.9114922","url":null,"abstract":"Efficient arrangement of UAVs in a swarm formation is essential to the functioning of the swarm as a temporary communication network. Such a network could assist in search and rescue efforts by providing first responders with a means of communication. We propose a user-friendly and effective system for calculating and visualizing an optimal layout of UAVs. An initial calculation to gather parameter information is followed by the proposed algorithm that generates an optimal solution. A visualization is displayed in an easy-to-comprehend manner after the proposed iterative genetic algorithm finds an optimal solution. The proposed system runs iteratively, adding UAV at each intermediate conclusion, until a solution is found. Information is passed between runs of the iterative genetic algorithm to reduce runtime and complexity. The results from testing show that the proposed algorithm yields optimal solutions more frequently than the k-means clustering algorithm. This system finds an optimal solution 80% of the time while k-means clustering is unable to find a solution when presented with a complex problem.","PeriodicalId":187607,"journal":{"name":"2020 29th Wireless and Optical Communications Conference (WOCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129771143","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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