N. Khalilzad, M. Ashjaei, L. Almeida, M. Behnam, Thomas Nolte
In this paper we present our ongoing work on developing a framework supporting adaptive resource reservations targeting component-based distributed real-time systems. The components may be spread over different resources in a distributed system. The proposed framework utilizes a reservation-based scheduling technique in which the sizes of reservations are adjusted during run-time to deal with dynamic resource demands of the software components. We present our modeling approach, we describe design options made and we present corresponding challenges.
{"title":"Towards adaptive resource reservations for component-based distributed real-time systems","authors":"N. Khalilzad, M. Ashjaei, L. Almeida, M. Behnam, Thomas Nolte","doi":"10.1145/2815482.2815486","DOIUrl":"https://doi.org/10.1145/2815482.2815486","url":null,"abstract":"In this paper we present our ongoing work on developing a framework supporting adaptive resource reservations targeting component-based distributed real-time systems. The components may be spread over different resources in a distributed system. The proposed framework utilizes a reservation-based scheduling technique in which the sizes of reservations are adjusted during run-time to deal with dynamic resource demands of the software components. We present our modeling approach, we describe design options made and we present corresponding challenges.","PeriodicalId":37024,"journal":{"name":"ACM SIGBED Review","volume":"12 1","pages":"24 - 27"},"PeriodicalIF":0.0,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2815482.2815486","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63940727","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 a modern industrial environment control programs are distributed among several devices. This raises new challenges, especially in handling the failure modes. Automatic reconfiguration is a possible approach in dealing with partial failures. The authors have proposed an IEC 61499 based replication framework for building fault tolerant applications - thus a failure of one sub-component does not to jeopardize the execution of the whole application. The proposed framework is capable of supporting dynamic reconfiguration on all automation levels in an industrial cell in order to patronage a fault tolerant and seamless production line.
{"title":"Tolerating partial failures on IEC 61499 applications","authors":"M. Sousa, C. Chrysoulas, Aydin E. Homay","doi":"10.1145/2815482.2815488","DOIUrl":"https://doi.org/10.1145/2815482.2815488","url":null,"abstract":"In a modern industrial environment control programs are distributed among several devices. This raises new challenges, especially in handling the failure modes. Automatic reconfiguration is a possible approach in dealing with partial failures. The authors have proposed an IEC 61499 based replication framework for building fault tolerant applications - thus a failure of one sub-component does not to jeopardize the execution of the whole application. The proposed framework is capable of supporting dynamic reconfiguration on all automation levels in an industrial cell in order to patronage a fault tolerant and seamless production line.","PeriodicalId":37024,"journal":{"name":"ACM SIGBED Review","volume":"12 1","pages":"32 - 35"},"PeriodicalIF":0.0,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2815482.2815488","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63941018","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}
Reliable multicast over wireless poses interesting challenges arising from the unreliable nature of the wireless medium. Recovering lost packets is particularly challenging in multicast scenarios since different receivers lose different packets. For this reason, simply retransmitting packets does not scale well with the number of receivers and particularly with the packet loss rate. A more efficient alternative is to use erasure codes to generate packets that can help many receivers at the same time. In this paper, we propose using online network coding to send coded packets that repair losses according to feedback reports sent by the clients. In particular, we propose using a recently developed scheduler for controlling feedback reports, which also allows differentiating the QoS provided to clients, and combine it with an online coding approach to provide novel stochastic guarantees of worst-case delay as required for QoS sensitive applications. We show preliminary simulation results that confirm the bounded decoding delay of our approach in a streaming application.
{"title":"Merging network coding with feedback management in multicast streaming","authors":"André Moreira, Luís Almeida, D. Lucani","doi":"10.1145/2815482.2815492","DOIUrl":"https://doi.org/10.1145/2815482.2815492","url":null,"abstract":"Reliable multicast over wireless poses interesting challenges arising from the unreliable nature of the wireless medium. Recovering lost packets is particularly challenging in multicast scenarios since different receivers lose different packets. For this reason, simply retransmitting packets does not scale well with the number of receivers and particularly with the packet loss rate. A more efficient alternative is to use erasure codes to generate packets that can help many receivers at the same time. In this paper, we propose using online network coding to send coded packets that repair losses according to feedback reports sent by the clients. In particular, we propose using a recently developed scheduler for controlling feedback reports, which also allows differentiating the QoS provided to clients, and combine it with an online coding approach to provide novel stochastic guarantees of worst-case delay as required for QoS sensitive applications. We show preliminary simulation results that confirm the bounded decoding delay of our approach in a streaming application.","PeriodicalId":37024,"journal":{"name":"ACM SIGBED Review","volume":"12 1","pages":"49 - 52"},"PeriodicalIF":0.0,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/2815482.2815492","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63941437","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}
Routing protocols in wireless sensor networks (WSN) face two main challenges: first, the challenging environments in which WSN's are deployed negatively affect the quality of the routing process. Therefore, routing protocols for WSN's should recognize and react to node failures and packet losses. Second, sensor nodes are battery-powered, which makes power a scarce resource. Routing protocols should optimize power consumption to prolong the lifetime of the WSN. In this paper, we present a new adaptive routing protocol for WSN's, we call it M2RC. M2RC has two phases: mesh establishment phase and data forwarding phase. In the first phase, M2RC establishes the routing state to enable multipath data forwarding. In the second phase, M2RC forwards data packets from the source to the sink. Targeting hop-by-hop reliability, an M2RC forwarding node waits for an acknowledgement (ACK) that its packets were correctly received at the next neighbor. Based on this feedback, an M2RC node applies multiplicative-increase/additive-decrease (MIAD) to control the number of neighbors targeted by its packet broadcast. We simulated M2RC in the ns-2 simulator [4] and compared it to GRAB [1], Max-power, and Min-power routing schemes. Our simulations show that M2RC achieves the highest throughput with at least 10-30% less consumed power per delivered report in scenarios where a certain numberof nodes unexpectedly fail.-
{"title":"M2RC: multiplicative-increase/additive-decrease multipath routing control for wireless sensor networks","authors":"Hany Morcos, I. Matta, Azer Bestavros","doi":"10.1145/1121782.1121786","DOIUrl":"https://doi.org/10.1145/1121782.1121786","url":null,"abstract":"Routing protocols in wireless sensor networks (WSN) face two main challenges: first, the challenging environments in which WSN's are deployed negatively affect the quality of the routing process. Therefore, routing protocols for WSN's should recognize and react to node failures and packet losses. Second, sensor nodes are battery-powered, which makes power a scarce resource. Routing protocols should optimize power consumption to prolong the lifetime of the WSN. In this paper, we present a new adaptive routing protocol for WSN's, we call it M2RC. M2RC has two phases: mesh establishment phase and data forwarding phase. In the first phase, M2RC establishes the routing state to enable multipath data forwarding. In the second phase, M2RC forwards data packets from the source to the sink. Targeting hop-by-hop reliability, an M2RC forwarding node waits for an acknowledgement (ACK) that its packets were correctly received at the next neighbor. Based on this feedback, an M2RC node applies multiplicative-increase/additive-decrease (MIAD) to control the number of neighbors targeted by its packet broadcast. We simulated M2RC in the ns-2 simulator [4] and compared it to GRAB [1], Max-power, and Min-power routing schemes. Our simulations show that M2RC achieves the highest throughput with at least 10-30% less consumed power per delivered report in scenarios where a certain numberof nodes unexpectedly fail.-","PeriodicalId":37024,"journal":{"name":"ACM SIGBED Review","volume":"2 1","pages":"13-18"},"PeriodicalIF":0.0,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/1121782.1121786","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64076811","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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