Pub Date : 2018-05-07DOI: 10.23919/WIOPT.2018.8362844
Shan Qu, Jinbei Zhang, Xinbing Wang
Distributed storage systems provide reliability by distributing data over multiple storage nodes. Once a node fails, a new node is introduced to the system to maintain the availability of the stored data. The new node downloads information from other surviving nodes called helper nodes to recover the lost data in the failed node. The number of helper nodes is called repair degree. Compared to traditional approaches, e.g., replication and erasure codes, the regenerating codes proposed recently can significantly reduce the repair bandwidth in homogeneous distributed storage systems. Most existing works focus on uniform settings (e.g., in terms of repair degree and repair bandwidth). However, due to network structures or connectivity limitations, for each failed node, the number of required helper nodes may be different for distinct failed nodes. Furthermore, considering the limits of network traffic of bandwidth, the amount of information allowed to be downloaded from each helper node could also vary. Thus we are motivated to investigate heterogeneous distributed storage systems where the repair degree and the amount of information downloaded from each helper node can be different. In order to obtain the minimal bandwidth to recover a failed node, we construct an information flow graph for such heterogeneous systems. By analyzing the cut-set bound of the information flow graph, the optimal tradeoff between storage capacity and repair bandwidth is derived. We then propose asymmetric regenerating codes that can achieve the curve of the optimal tradeoff. A linear construction of asymmetric regenerating codes is presented. Compared with previous regenerating codes, asymmetric regenerating codes are shown to have a lower repair bandwidth under a certain constraint condition, whose reduction can be up to 36.2%.
{"title":"Asymmetric regenerating codes for heterogeneous distributed storage systems","authors":"Shan Qu, Jinbei Zhang, Xinbing Wang","doi":"10.23919/WIOPT.2018.8362844","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362844","url":null,"abstract":"Distributed storage systems provide reliability by distributing data over multiple storage nodes. Once a node fails, a new node is introduced to the system to maintain the availability of the stored data. The new node downloads information from other surviving nodes called helper nodes to recover the lost data in the failed node. The number of helper nodes is called repair degree. Compared to traditional approaches, e.g., replication and erasure codes, the regenerating codes proposed recently can significantly reduce the repair bandwidth in homogeneous distributed storage systems. Most existing works focus on uniform settings (e.g., in terms of repair degree and repair bandwidth). However, due to network structures or connectivity limitations, for each failed node, the number of required helper nodes may be different for distinct failed nodes. Furthermore, considering the limits of network traffic of bandwidth, the amount of information allowed to be downloaded from each helper node could also vary. Thus we are motivated to investigate heterogeneous distributed storage systems where the repair degree and the amount of information downloaded from each helper node can be different. In order to obtain the minimal bandwidth to recover a failed node, we construct an information flow graph for such heterogeneous systems. By analyzing the cut-set bound of the information flow graph, the optimal tradeoff between storage capacity and repair bandwidth is derived. We then propose asymmetric regenerating codes that can achieve the curve of the optimal tradeoff. A linear construction of asymmetric regenerating codes is presented. Compared with previous regenerating codes, asymmetric regenerating codes are shown to have a lower repair bandwidth under a certain constraint condition, whose reduction can be up to 36.2%.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"2018 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114268076","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362848
Bin Li, Zai Shi, A. Eryilmaz
There is a rich theory and plethora of algorithms in the literature aiming at the efficient scheduling of stochastic networks. These solutions are predominantly designed under the assumption of traffic demands that are independently generated at network nodes, without any requirement for synchronization among their received services. In this work, we note that many applications, including cloud computing, virtual reality, gaming, autonomous vehicular networks and collaborative design, generate traffic simultaneously at multiple nodes when they arrive, with possibly non-uniform file sizes, whose performance relies on the synchronous completion of the traffic across the network. This calls for the design of new scheduling algorithms that aims to coordinate the service of packets of the same traffic across the network. Towards this end, we propose a novel scheduling algorithm that not only accounts for the heterogeneity of the file size distributions, but also works towards synchronizing the completion time of the same traffic stream across the network. This is achieved by employing two insights that emanate from key motivating examples we develop: (1) the normalization of traffic load with respect to the non-uniform file sizes; and (2) the incorporation of deviation of normalized loads across network nodes that serve synchronized traffic. After establishing the throughput-optimality of our algorithm in general stochastic networks, we perform extensive simulations under various (spanning both wired and wireless) settings to reveal the potential completion time gains that it yields over other throughput-optimal strategies designed under the assumption of independent traffic generation.
{"title":"Efficient scheduling for synchronized demands in stochastic networks","authors":"Bin Li, Zai Shi, A. Eryilmaz","doi":"10.23919/WIOPT.2018.8362848","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362848","url":null,"abstract":"There is a rich theory and plethora of algorithms in the literature aiming at the efficient scheduling of stochastic networks. These solutions are predominantly designed under the assumption of traffic demands that are independently generated at network nodes, without any requirement for synchronization among their received services. In this work, we note that many applications, including cloud computing, virtual reality, gaming, autonomous vehicular networks and collaborative design, generate traffic simultaneously at multiple nodes when they arrive, with possibly non-uniform file sizes, whose performance relies on the synchronous completion of the traffic across the network. This calls for the design of new scheduling algorithms that aims to coordinate the service of packets of the same traffic across the network. Towards this end, we propose a novel scheduling algorithm that not only accounts for the heterogeneity of the file size distributions, but also works towards synchronizing the completion time of the same traffic stream across the network. This is achieved by employing two insights that emanate from key motivating examples we develop: (1) the normalization of traffic load with respect to the non-uniform file sizes; and (2) the incorporation of deviation of normalized loads across network nodes that serve synchronized traffic. After establishing the throughput-optimality of our algorithm in general stochastic networks, we perform extensive simulations under various (spanning both wired and wireless) settings to reveal the potential completion time gains that it yields over other throughput-optimal strategies designed under the assumption of independent traffic generation.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124249708","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362806
Jeongho Kwak, G. Paschos, G. Iosifidis
With elastic CDNs, content providers can rent cache space on demand at different cloud locations in order to enhance their offered quality of service (QoS). This paper addresses a key challenge in this context, namely how to invest an available budget in cache space in order to match spatio-temporal fluctuations of file demand and storage price. Specifically, we consider jointly dynamic cache rental, file placement, and request-cache association in a wireless scenario in order to provide a just-in-time CDN service. The objective is to maximize the benefit in average download delay obtained by the rented caches, while ensuring that the time-average rental cost is less than a fixed budget. We leverage a Lyapunov drift-minus-benefit technique to transform our infinite horizon problem into day-by-day subproblems which can be solved without knowledge of distant future file popularity and transmission rates. For the case of non-overlapping small cells (also wired case) we provide an efficient subproblem solution, referred to as JCC. However, in the general overlapping case, the subproblem becomes a mixed integer non-linear program (MINLP). In this case, we employ a dual decomposition method to derive a scalable solution, namely the JCCA algorithm. Finally, via extensive simulations, we reveal that the proposed JCCA algorithm attains 82.66 % higher delay benefit than existing static cache storage-based algorithms when available average cache budget is 20% of entire file library; moreover, the benefit becomes higher as the average cache budget gets tighter.
{"title":"Dynamic cache rental and content caching in elastic wireless CDNs","authors":"Jeongho Kwak, G. Paschos, G. Iosifidis","doi":"10.23919/WIOPT.2018.8362806","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362806","url":null,"abstract":"With elastic CDNs, content providers can rent cache space on demand at different cloud locations in order to enhance their offered quality of service (QoS). This paper addresses a key challenge in this context, namely how to invest an available budget in cache space in order to match spatio-temporal fluctuations of file demand and storage price. Specifically, we consider jointly dynamic cache rental, file placement, and request-cache association in a wireless scenario in order to provide a just-in-time CDN service. The objective is to maximize the benefit in average download delay obtained by the rented caches, while ensuring that the time-average rental cost is less than a fixed budget. We leverage a Lyapunov drift-minus-benefit technique to transform our infinite horizon problem into day-by-day subproblems which can be solved without knowledge of distant future file popularity and transmission rates. For the case of non-overlapping small cells (also wired case) we provide an efficient subproblem solution, referred to as JCC. However, in the general overlapping case, the subproblem becomes a mixed integer non-linear program (MINLP). In this case, we employ a dual decomposition method to derive a scalable solution, namely the JCCA algorithm. Finally, via extensive simulations, we reveal that the proposed JCCA algorithm attains 82.66 % higher delay benefit than existing static cache storage-based algorithms when available average cache budget is 20% of entire file library; moreover, the benefit becomes higher as the average cache budget gets tighter.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132057987","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362858
Rohit Kumar, Ankit Yadav, S. Darak, M. Hanawal
An opportunistic spectrum access (OSA) in the infrastructure-less network has received significant attention in last few years due to their ability to improve spectrum utilization as well as usefulness in the infrastructure-less networks established for disaster relief and military applications. The main research problem for feasible implementation of such network is to achieve coordination among secondary users (SUs) (i.e. unlicensed users). Existing algorithms incur a significant number of collisions which in turn require retransmissions and hence, lead to inefficient use of battery power, spectrum and time. In this paper, we set-up the problem as a multi-player Bandit and develop a new distributed algorithm which allows SUs to select one of the top channels with a significantly fewer number of collisions. We show that the proposed algorithm has constant regret with high confidence. We validate our claims and the superiority of the proposed algorithm over existing state-of-the-art algorithms through the exhaustive simulated experiments as well as a realistic USRP based experiments in the real radio environment.
{"title":"Trekking based distributed algorithm for opportunistic spectrum access in infrastructure-less network","authors":"Rohit Kumar, Ankit Yadav, S. Darak, M. Hanawal","doi":"10.23919/WIOPT.2018.8362858","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362858","url":null,"abstract":"An opportunistic spectrum access (OSA) in the infrastructure-less network has received significant attention in last few years due to their ability to improve spectrum utilization as well as usefulness in the infrastructure-less networks established for disaster relief and military applications. The main research problem for feasible implementation of such network is to achieve coordination among secondary users (SUs) (i.e. unlicensed users). Existing algorithms incur a significant number of collisions which in turn require retransmissions and hence, lead to inefficient use of battery power, spectrum and time. In this paper, we set-up the problem as a multi-player Bandit and develop a new distributed algorithm which allows SUs to select one of the top channels with a significantly fewer number of collisions. We show that the proposed algorithm has constant regret with high confidence. We validate our claims and the superiority of the proposed algorithm over existing state-of-the-art algorithms through the exhaustive simulated experiments as well as a realistic USRP based experiments in the real radio environment.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114287786","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362808
Zhiyuan Wang, Lin Gao, Jianwei Huang
Today, many mobile network operators (MNOs) provide data services through a three-part tariff data plan, which involves a fixed subscription fee, a data cap, and a per-unit fee for the data over-usage exceeding the data cap. To increase their market competitiveness, MNOs have been trying to provide more time flexibility in the data plans. One of such innovations is the rollover data plan, which allows a subscriber to use the unused data of the previous month in the current month. Depending on the consumption priority of the rollover data, different rollover data plans can have different levels of time flexibility. The interactions among multiple MNOs offering rollover data plans, however, are quite complicated and sometimes counter-intuitive. To examine this issue, in this paper we build a simple market model of two MNOs competing to serve the same pool of heterogeneous users. We formulate the market competition as a two-stage game: in Stage I, the MNOs simultaneously decide their pricing strategies of their chosen data mechanisms; In Stage II, users make their subscription decisions among the two MNOs. We characterize the sub-game perfect equilibrium (SPE) of the two-stage game through backward induction. Comparing with a monopoly market where a better time flexibility always improves the MNO's profit, our analysis reveals a rather complicated story in the duopoly market: (i) with a mild competition, the stronger MNO will increase both MNOs' profits by adopting a data plan with a better time flexibility, while the weaker MNO will decrease both MNOs' profits by adopting a data plan with a better time flexibility; (ii) with a fierce competition, any MNO will increase its profit and decrease the competitor's profit by adopting a data plan with a better time flexibility.
{"title":"Pricing competition of rollover data plan","authors":"Zhiyuan Wang, Lin Gao, Jianwei Huang","doi":"10.23919/WIOPT.2018.8362808","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362808","url":null,"abstract":"Today, many mobile network operators (MNOs) provide data services through a three-part tariff data plan, which involves a fixed subscription fee, a data cap, and a per-unit fee for the data over-usage exceeding the data cap. To increase their market competitiveness, MNOs have been trying to provide more time flexibility in the data plans. One of such innovations is the rollover data plan, which allows a subscriber to use the unused data of the previous month in the current month. Depending on the consumption priority of the rollover data, different rollover data plans can have different levels of time flexibility. The interactions among multiple MNOs offering rollover data plans, however, are quite complicated and sometimes counter-intuitive. To examine this issue, in this paper we build a simple market model of two MNOs competing to serve the same pool of heterogeneous users. We formulate the market competition as a two-stage game: in Stage I, the MNOs simultaneously decide their pricing strategies of their chosen data mechanisms; In Stage II, users make their subscription decisions among the two MNOs. We characterize the sub-game perfect equilibrium (SPE) of the two-stage game through backward induction. Comparing with a monopoly market where a better time flexibility always improves the MNO's profit, our analysis reveals a rather complicated story in the duopoly market: (i) with a mild competition, the stronger MNO will increase both MNOs' profits by adopting a data plan with a better time flexibility, while the weaker MNO will decrease both MNOs' profits by adopting a data plan with a better time flexibility; (ii) with a fierce competition, any MNO will increase its profit and decrease the competitor's profit by adopting a data plan with a better time flexibility.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129652680","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362862
Chun-Hung Liu
Consider a decentralized device-to-device (D2D) network consisting of K different types of D2D pairs in which the D2D pairs of each specific type form an independent homogeneous Poisson point process (PPP) and the transmitter (TX) of each D2D pair has a unique intended receiver (RX). For this heterogeneous network model, we develop a model-free tractable framework to analyze the coverage probability without any specific model assumptions for channel fading, stochastic transmit power and distance. First we device a novel approach to finding the Laplace transform of the reciprocal of the SIR which is used to characterize the model-free coverage probability of the D2D pair of each type. Our main analytical findings show that the model-free bounds of the coverage probability can be obtained and they reduce to a closed-form result as long as the received signal power has an Erlang distribution. These findings are applied to expound when the randomness of the received signal power benefits/jeopardizes the coverage probability and how to use the distributed stochastic power control to improve the coverage probability of each D2D pair.
{"title":"A model-free framework for coverage evaluation in device-to-device heterogeneous networks","authors":"Chun-Hung Liu","doi":"10.23919/WIOPT.2018.8362862","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362862","url":null,"abstract":"Consider a decentralized device-to-device (D2D) network consisting of K different types of D2D pairs in which the D2D pairs of each specific type form an independent homogeneous Poisson point process (PPP) and the transmitter (TX) of each D2D pair has a unique intended receiver (RX). For this heterogeneous network model, we develop a model-free tractable framework to analyze the coverage probability without any specific model assumptions for channel fading, stochastic transmit power and distance. First we device a novel approach to finding the Laplace transform of the reciprocal of the SIR which is used to characterize the model-free coverage probability of the D2D pair of each type. Our main analytical findings show that the model-free bounds of the coverage probability can be obtained and they reduce to a closed-form result as long as the received signal power has an Erlang distribution. These findings are applied to expound when the randomness of the received signal power benefits/jeopardizes the coverage probability and how to use the distributed stochastic power control to improve the coverage probability of each D2D pair.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127893943","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362883
Guangsheng Feng, Teng Li, Dongdong Su, Haibin Lv, Huiqiang Wang, Hongwu Lv
Device-to-device (D2D) communication is a promising technique for traffic offloading in next-generation cellular systems. In this paper, we study the D2D-assisted cellular traffic offloading (DACTO) problem, where Wi-Fi Direct technology is employed in D2D communication in consideration of its wide communication coverage and high transmission rate. Taking into account the user traffic demands and population distributions, we formulate the DACTO problem as a "Min-Max" problem, in which the operator energy consumption is minimized and meanwhile the user satisfaction is maximized. The DACTO is proven to be a NP-complete problem and is difficult to tackle with the increasing number of population. To achieve a feasible solution, we convert the DACTO problem into an approximate combination optimization problem, and develop a backpack algorithm combined with an improved Hungarian algorithm to solve it. Simulation results show that the proposed method achieves the near-optimal solution for the DACTO problem.
{"title":"A joint optimization method for data offloading in D2D-enabled cellular networks","authors":"Guangsheng Feng, Teng Li, Dongdong Su, Haibin Lv, Huiqiang Wang, Hongwu Lv","doi":"10.23919/WIOPT.2018.8362883","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362883","url":null,"abstract":"Device-to-device (D2D) communication is a promising technique for traffic offloading in next-generation cellular systems. In this paper, we study the D2D-assisted cellular traffic offloading (DACTO) problem, where Wi-Fi Direct technology is employed in D2D communication in consideration of its wide communication coverage and high transmission rate. Taking into account the user traffic demands and population distributions, we formulate the DACTO problem as a \"Min-Max\" problem, in which the operator energy consumption is minimized and meanwhile the user satisfaction is maximized. The DACTO is proven to be a NP-complete problem and is difficult to tackle with the increasing number of population. To achieve a feasible solution, we convert the DACTO problem into an approximate combination optimization problem, and develop a backpack algorithm combined with an improved Hungarian algorithm to solve it. Simulation results show that the proposed method achieves the near-optimal solution for the DACTO problem.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130334079","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362812
Sherif ElAzzouni, E. Ekici, N. Shroff
The rapid growth of mobile data traffic is straining cellular networks. A natural approach to alleviate cellular networks congestion is to use, in addition to the cellular interface, secondary interfaces such as WiFi, Dynamic spectrum and mmWave to aid cellular networks in handling mobile traffic. The fundamental question now becomes: How should traffic be distributed over different interfaces, taking into account different application QoS requirements and the diverse nature of radio interfaces. To this end, we propose the Discounted Rate Utility Maximization (DRUM) framework with interface costs as a means to quantify application preferences in terms of throughput, delay, and cost. The flow rate allocation problem can be formulated as a convex optimization problem. However, solving this problem requires non-causal knowledge of the time-varying capacities of all radio interfaces. To this end, we propose an online predictive algorithm that exploits the predictability of wireless connectivity for a small look-ahead window w. We show that, under some mild conditions, the proposed algorithm achieves a constant competitive ratio independent of the time horizon T. Furthermore, the competitive ratio approaches 1 as the prediction window increases. We also propose another predictive algorithm based on the "Receding Horizon Control" principle from control theory that performs very well in practice. Numerical simulations serve to validate our formulation, by showing that under the DRUM framework: the more delay-tolerant the flow, the less it uses the cellular network, preferring to transmit in high rate bursts over the secondary interfaces. Conversely, delay-sensitive flows consistently transmit irrespective of different interfaces' availability. Simulations also show that the proposed online predictive algorithms have a near-optimal performance compared to the offline prescient solution under all considered scenarios.
{"title":"Qos-aware predictive rate allocation over heterogeneous wireless interfaces","authors":"Sherif ElAzzouni, E. Ekici, N. Shroff","doi":"10.23919/WIOPT.2018.8362812","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362812","url":null,"abstract":"The rapid growth of mobile data traffic is straining cellular networks. A natural approach to alleviate cellular networks congestion is to use, in addition to the cellular interface, secondary interfaces such as WiFi, Dynamic spectrum and mmWave to aid cellular networks in handling mobile traffic. The fundamental question now becomes: How should traffic be distributed over different interfaces, taking into account different application QoS requirements and the diverse nature of radio interfaces. To this end, we propose the Discounted Rate Utility Maximization (DRUM) framework with interface costs as a means to quantify application preferences in terms of throughput, delay, and cost. The flow rate allocation problem can be formulated as a convex optimization problem. However, solving this problem requires non-causal knowledge of the time-varying capacities of all radio interfaces. To this end, we propose an online predictive algorithm that exploits the predictability of wireless connectivity for a small look-ahead window w. We show that, under some mild conditions, the proposed algorithm achieves a constant competitive ratio independent of the time horizon T. Furthermore, the competitive ratio approaches 1 as the prediction window increases. We also propose another predictive algorithm based on the \"Receding Horizon Control\" principle from control theory that performs very well in practice. Numerical simulations serve to validate our formulation, by showing that under the DRUM framework: the more delay-tolerant the flow, the less it uses the cellular network, preferring to transmit in high rate bursts over the secondary interfaces. Conversely, delay-sensitive flows consistently transmit irrespective of different interfaces' availability. Simulations also show that the proposed online predictive algorithms have a near-optimal performance compared to the offline prescient solution under all considered scenarios.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115241389","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362856
Subrahmanya Swamy Peruru, A. Srinivasan, R. Ganti, K. Jagannathan
We propose distributed scheduling algorithms that guarantee a constant fraction of the maximum throughput for typical wireless topologies, and have O(1) delay and complexity in the network size. Our algorithms resolve collisions among pairs of conflicting nodes by assigning a master-slave hierarchy. When the master-slave hierarchy is chosen randomly, our algorithm matches the throughput performance of the maximal scheduling policies, with a complexity and delay that do not scale with network size. When the master-slave hierarchy is chosen based on the network topology, the throughput performance of our algorithm is characterized by a parameter of the conflict graph called the master-interference degree. For commonly used conflict graph topologies, our results lead to the best known throughput guarantees among the algorithms that have O(1) delay and complexity. Numerical results indicate that our algorithms out-perform the existing O(1) complexity algorithms like Q-CSMA.
{"title":"Hierarchical scheduling algorithms with throughput guarantees and low delay","authors":"Subrahmanya Swamy Peruru, A. Srinivasan, R. Ganti, K. Jagannathan","doi":"10.23919/WIOPT.2018.8362856","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362856","url":null,"abstract":"We propose distributed scheduling algorithms that guarantee a constant fraction of the maximum throughput for typical wireless topologies, and have O(1) delay and complexity in the network size. Our algorithms resolve collisions among pairs of conflicting nodes by assigning a master-slave hierarchy. When the master-slave hierarchy is chosen randomly, our algorithm matches the throughput performance of the maximal scheduling policies, with a complexity and delay that do not scale with network size. When the master-slave hierarchy is chosen based on the network topology, the throughput performance of our algorithm is characterized by a parameter of the conflict graph called the master-interference degree. For commonly used conflict graph topologies, our results lead to the best known throughput guarantees among the algorithms that have O(1) delay and complexity. Numerical results indicate that our algorithms out-perform the existing O(1) complexity algorithms like Q-CSMA.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121330194","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 : 2018-05-07DOI: 10.23919/WIOPT.2018.8362819
Yeongjin Kim, Hyang-Won Lee, S. Chong
Network function virtualization (NFV) and Computation offloading (CO) are state-of-the-art technologies for flexible utilization of networking and processing resources. These two technologies are closely related in that they enable multiple physical entities to process a function provided in a service, and the service (or end host) chooses which resources to use. In this paper, we propose a generalized dual-resource system, which unifies NFV service and CO service frameworks, and formulate a multi-path problem for choosing resources to use in NFV and CO services. The problem is reformulated as a variational inequality by using Lagrange dual theory and saddle point theory. Based on this formulation, we propose an extragradient-based algorithm that controls and splits the sending rate of a service. We prove that the algorithm converges to an optimal point where system cost minus service utility is minimized. Simulations under diverse scenarios demonstrate that our algorithm achieves high quality of service while reducing the system cost by jointly considering dual-resource coupling and service characteristics.
网络功能虚拟化(Network function virtualization, NFV)和计算卸载(Computation offloading, CO)是一种灵活利用网络和处理资源的技术。这两种技术密切相关，因为它们使多个物理实体能够处理服务中提供的功能，并且服务(或终端主机)选择使用哪些资源。本文提出了一种统一NFV服务和CO服务框架的广义双资源体系，并提出了NFV和CO服务中资源选择的多路径问题。利用拉格朗日对偶理论和鞍点理论，将该问题重新表述为变分不等式。在此基础上，我们提出了一种基于提取的算法来控制和分割服务的发送速率。证明了该算法收敛于系统成本-服务效用最小的最优点。多种场景下的仿真结果表明，该算法综合考虑了双资源耦合和服务特性，在降低系统成本的同时实现了高质量的服务。
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