Pub Date : 2018-05-07DOI: 10.23919/WIOPT.2018.8362879
Shujuan You, Xiaotao Li, Wai Chen
Intelligent interactions of IoT mean that devices can perform proper actions and communicate with each other to support specific application scenarios without human intervention. To do this, the biggest challenge is providing IoT objects with common knowledge and abilities to analyze data and to reason. In this paper, we present a semantic mechanism to realize intelligent interactions of IoT devices on account of the semantic knowledge and machine learning technology. Based on this mechanism, a three-layer IoT system named IoT-Book is built, and every action performed by a device is deduced through analyzing the environment data and personalized preferences of the user. Finally, a smart home use case is demonstrated, and our approach is proved to be effective.
{"title":"A semantic mechanism for Internet-of-Things (IoT) to implement intelligent interactions","authors":"Shujuan You, Xiaotao Li, Wai Chen","doi":"10.23919/WIOPT.2018.8362879","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362879","url":null,"abstract":"Intelligent interactions of IoT mean that devices can perform proper actions and communicate with each other to support specific application scenarios without human intervention. To do this, the biggest challenge is providing IoT objects with common knowledge and abilities to analyze data and to reason. In this paper, we present a semantic mechanism to realize intelligent interactions of IoT devices on account of the semantic knowledge and machine learning technology. Based on this mechanism, a three-layer IoT system named IoT-Book is built, and every action performed by a device is deduced through analyzing the environment data and personalized preferences of the user. Finally, a smart home use case is demonstrated, and our approach is proved to be effective.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"32 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":"122060139","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.2018.8362853
Suneet Sawant, M. Hanawal, S. Darak, Rohit Kumar
Efficient utilization of licensed spectrum in the cognitive radio network is challenging due to lack of coordination among the Secondary Users (SUs). Distributed algorithms proposed in the literature aim to maximize the network throughput by ensuring orthogonal channel allocation for the SUs. However, these algorithms work under the assumption that all the SUs faithfully follow the algorithms which may not always hold due to the decentralized nature of the network. Moreover, they are vulnerable to Denial of Service attacks. In this paper, we study distributed algorithms that are robust against malicious behavior (jamming attack). We consider jammers launching coordinated attack where they select non-overlapping channels in each time slot and can lead to significantly higher number of collisions for SUs than uncoordinated attack. We setup the problem as a multiplayer bandit and develop distributed learning algorithms. The analysis shows that when the SUs faithfully implement proposed algorithms, the regret is constant with high probability. We validate our claims through exhaustive synthetic experiments and also through a realistic USRP based experiments.
{"title":"Distributed learning algorithms for coordination in a cognitive network in presence of jammers","authors":"Suneet Sawant, M. Hanawal, S. Darak, Rohit Kumar","doi":"10.23919/WIOPT.2018.8362853","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362853","url":null,"abstract":"Efficient utilization of licensed spectrum in the cognitive radio network is challenging due to lack of coordination among the Secondary Users (SUs). Distributed algorithms proposed in the literature aim to maximize the network throughput by ensuring orthogonal channel allocation for the SUs. However, these algorithms work under the assumption that all the SUs faithfully follow the algorithms which may not always hold due to the decentralized nature of the network. Moreover, they are vulnerable to Denial of Service attacks. In this paper, we study distributed algorithms that are robust against malicious behavior (jamming attack). We consider jammers launching coordinated attack where they select non-overlapping channels in each time slot and can lead to significantly higher number of collisions for SUs than uncoordinated attack. We setup the problem as a multiplayer bandit and develop distributed learning algorithms. The analysis shows that when the SUs faithfully implement proposed algorithms, the regret is constant with high probability. We validate our claims through exhaustive synthetic experiments and also through a realistic USRP based experiments.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"334 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":"124306125","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.2018.8362807
Guopeng Zhang, Jiansheng Qian, Shuo Xiao, Jie Gu
Machine-to-machine (M2M) type communications (MTCs) over cellular networks feature the large number of MTC devices (MTCDs), small and time controlled data transmissions, and rigorous energy limitation. Considering full-duplex (FD) relaying can achieve high spectrum and energy efficiency, this paper proposes an MTC-enabled cellular communication scheme, where a traditional cellular user equipment (UE) is configured as an FD relaying based gateway to assist the uplink transmissions of the served MTCDs. The designed objective is to minimize the aggregate energy consumption of a group consisting of a UE and multiple MTCDs, while fulfilling their minimum throughput requirements. To this end, a convex optimization problem is formulated and a low complexity algorithm is also developed to find the optimal power allocation strategies for the UE and the MTCDs. The simulation results show that the proposed scheme can achieve most of the channel reuse gain of the FD relaying if the self-interference at the UE is controlled below a certain level.
{"title":"Hierarchical resource allocation scheme for M2M communications enabled by cellular networks","authors":"Guopeng Zhang, Jiansheng Qian, Shuo Xiao, Jie Gu","doi":"10.23919/WIOPT.2018.8362807","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362807","url":null,"abstract":"Machine-to-machine (M2M) type communications (MTCs) over cellular networks feature the large number of MTC devices (MTCDs), small and time controlled data transmissions, and rigorous energy limitation. Considering full-duplex (FD) relaying can achieve high spectrum and energy efficiency, this paper proposes an MTC-enabled cellular communication scheme, where a traditional cellular user equipment (UE) is configured as an FD relaying based gateway to assist the uplink transmissions of the served MTCDs. The designed objective is to minimize the aggregate energy consumption of a group consisting of a UE and multiple MTCDs, while fulfilling their minimum throughput requirements. To this end, a convex optimization problem is formulated and a low complexity algorithm is also developed to find the optimal power allocation strategies for the UE and the MTCDs. The simulation results show that the proposed scheme can achieve most of the channel reuse gain of the FD relaying if the self-interference at the UE is controlled below a certain level.","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":"134502113","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.2018.8362851
Altug Karakurt, A. Eryilmaz, C. E. Koksal
We consider the problem of detecting the active wireless stations among a very large population. This problem is highly relevant in applications involving passive and active RFID tags and dense IoT settings. The state of the art mainly utilizes interference avoiding (e.g., CSMA-based) approaches with the objective of identifying one station at a time. We first derive basic limits of the achievable delay with interference avoiding paradigm. Then, we consider the setting in which each station is assigned a signature sequence, picked at random from a specific alphabet and active stations transmit their signatures simultaneously upon activation. The challenge at the detector is to detect all active stations from the combined signature signal with low probability of misdetection and false positives. We show that, such an interference embracing approach can substantially reduce the detection delay, at an arbitrarily low probability of both types of detection errors, as the number of stations scale. We show that, under a randomized activation model the collision embracing detection scheme achieves Θ(log2(n)/log(log(n))) delay while the expected delay of existing CSMA schemes are Ω(log2(n)) for a population of n stations. Finally, we discuss large-scale implementation issues such as the design of low-complexity detection schemes and present numerical investigations.
{"title":"Quick discovery of mobile devices in the many-user regime — carrier sensing or simultaneous detection?","authors":"Altug Karakurt, A. Eryilmaz, C. E. Koksal","doi":"10.23919/WIOPT.2018.8362851","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362851","url":null,"abstract":"We consider the problem of detecting the active wireless stations among a very large population. This problem is highly relevant in applications involving passive and active RFID tags and dense IoT settings. The state of the art mainly utilizes interference avoiding (e.g., CSMA-based) approaches with the objective of identifying one station at a time. We first derive basic limits of the achievable delay with interference avoiding paradigm. Then, we consider the setting in which each station is assigned a signature sequence, picked at random from a specific alphabet and active stations transmit their signatures simultaneously upon activation. The challenge at the detector is to detect all active stations from the combined signature signal with low probability of misdetection and false positives. We show that, such an interference embracing approach can substantially reduce the detection delay, at an arbitrarily low probability of both types of detection errors, as the number of stations scale. We show that, under a randomized activation model the collision embracing detection scheme achieves Θ(log2(n)/log(log(n))) delay while the expected delay of existing CSMA schemes are Ω(log2(n)) for a population of n stations. Finally, we discuss large-scale implementation issues such as the design of low-complexity detection schemes and present numerical investigations.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"37 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":"115672545","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.2018.8362811
Xinping Xu, Lingjie Duan, Minming Li
Unmanned Aerial Vehicle (UAV) networks have emerged as a promising technique to rapidly provide wireless services to a group of mobile users simultaneously in the three-dimensional (3D) geographical space, where a flying UAV facility can be deployed closely based on users' 3D location reports. The paper aims to address a challenging issue that each user is selfish and prefers the UAV to be located as close to himself as possible, by misreporting his location and changing the optimal UAV location. We study the social planner's problem to determine the final deployment location of a UAV facility in a 3D space, by ensuring all selfish users' truthfulness in reporting their locations. To minimize the social service cost in this UAV placement game, we design a strategyproof mechanism with approximation ratio 2, when comparing to the social optimum. On the other hand, as the UAV to be deployed may interfere with another group of incumbent users in the same space, we also study the obnoxious UAV placement game to maximally keep their social utility, where each incumbent user may misreport his location to keep the UAV away from him. We propose a strategyproof mechanism with approximation ratio 5. Besides the worst-case analysis, we further analyze the empirical performances of the proposed mechanisms and show that they converge to the social optimum as the number of users becomes large. Finally, we extend to the dual-preference UAV placement game by considering the coexistence of the two groups of users, where users can misreport both their locations and preference types. We successfully propose a strategyproof mechanism with approximation ratio 8.
{"title":"UAV placement games for optimal wireless service provision","authors":"Xinping Xu, Lingjie Duan, Minming Li","doi":"10.23919/WIOPT.2018.8362811","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362811","url":null,"abstract":"Unmanned Aerial Vehicle (UAV) networks have emerged as a promising technique to rapidly provide wireless services to a group of mobile users simultaneously in the three-dimensional (3D) geographical space, where a flying UAV facility can be deployed closely based on users' 3D location reports. The paper aims to address a challenging issue that each user is selfish and prefers the UAV to be located as close to himself as possible, by misreporting his location and changing the optimal UAV location. We study the social planner's problem to determine the final deployment location of a UAV facility in a 3D space, by ensuring all selfish users' truthfulness in reporting their locations. To minimize the social service cost in this UAV placement game, we design a strategyproof mechanism with approximation ratio 2, when comparing to the social optimum. On the other hand, as the UAV to be deployed may interfere with another group of incumbent users in the same space, we also study the obnoxious UAV placement game to maximally keep their social utility, where each incumbent user may misreport his location to keep the UAV away from him. We propose a strategyproof mechanism with approximation ratio 5. Besides the worst-case analysis, we further analyze the empirical performances of the proposed mechanisms and show that they converge to the social optimum as the number of users becomes large. Finally, we extend to the dual-preference UAV placement game by considering the coexistence of the two groups of users, where users can misreport both their locations and preference types. We successfully propose a strategyproof mechanism with approximation ratio 8.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"7 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":"125716299","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.2018.8362847
Apostolos Destounis, G. Paschos, Jesús Arnau, M. Kountouris
This paper studies Ultra-Reliable Low-Latency Communications (URLLC), an important service class of emerging 5G networks. In this class, multiple unreliable transmissions must be combined to achieve reliable latency: a user experiences a frame success when the entire L bits are received correctly within a deadline, and its latency performance is reliable when the frame success rate is above a threshold. When jointly serving multiple users, a natural URLLC scheduling question arises: given the uncertainty of the wireless channel, can we find a scheduling policy that allows all users to meet a target reliable latency objective? This is called the URLLC SLA Satisfaction (USS) problem. The USS problem is an infinite horizon constrained Markov Decision Process, for which, after establishing a convenient property, we are able to derive an optimal policy based on dynamic programming. Our policy suffers from the curse of dimensionality, hence for large instances we propose a class of knapsack-inspired computationally efficient — but not necessarily optimal — policies. We prove that every policy in that class becomes optimal in a fluid regime, where both the deadline and L scale to infinity, while our simulations show that the policies perform well even in small practical instances of the USS problem.
{"title":"Scheduling URLLC users with reliable latency guarantees","authors":"Apostolos Destounis, G. Paschos, Jesús Arnau, M. Kountouris","doi":"10.23919/WIOPT.2018.8362847","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362847","url":null,"abstract":"This paper studies Ultra-Reliable Low-Latency Communications (URLLC), an important service class of emerging 5G networks. In this class, multiple unreliable transmissions must be combined to achieve reliable latency: a user experiences a frame success when the entire L bits are received correctly within a deadline, and its latency performance is reliable when the frame success rate is above a threshold. When jointly serving multiple users, a natural URLLC scheduling question arises: given the uncertainty of the wireless channel, can we find a scheduling policy that allows all users to meet a target reliable latency objective? This is called the URLLC SLA Satisfaction (USS) problem. The USS problem is an infinite horizon constrained Markov Decision Process, for which, after establishing a convenient property, we are able to derive an optimal policy based on dynamic programming. Our policy suffers from the curse of dimensionality, hence for large instances we propose a class of knapsack-inspired computationally efficient — but not necessarily optimal — policies. We prove that every policy in that class becomes optimal in a fluid regime, where both the deadline and L scale to infinity, while our simulations show that the policies perform well even in small practical instances of the USS problem.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"19 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":"127778817","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.2018.8362880
G. Haßlinger, Juho Heikkinen, K. Ntougias, Frank Hasslinger, O. Hohlfeld
We compare web caching strategies based on the least recently used (LRU) and the least frequently used (LFU) replacement principles with optimum caching according to Belady's algorithm. The achievable hit rates of the strategies are shown to improve with the exploited knowledge about the request pattern while the computation effort is also increasing. The results give an overview of performance tradeoffs in the whole relevant range for web caching with Zipf request pattern. In a second part, we study a combined approach of the optimum strategy for a limited look-ahead with LRU, LFU or other non-predictive methods. We evaluate the hit rate gain depending on the extent of the look-ahead for request traces and for the independent reference model (IRM) via simulation and derive an analytic confirmation of the observed behaviour. It is shown that caching for video streaming can benefit from the proposed look-ahead technique, when replacement decisions can be partly revised due to new requests being encountered during long lasting content updates.
{"title":"Optimum caching versus LRU and LFU: Comparison and combined limited look-ahead strategies","authors":"G. Haßlinger, Juho Heikkinen, K. Ntougias, Frank Hasslinger, O. Hohlfeld","doi":"10.23919/WIOPT.2018.8362880","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362880","url":null,"abstract":"We compare web caching strategies based on the least recently used (LRU) and the least frequently used (LFU) replacement principles with optimum caching according to Belady's algorithm. The achievable hit rates of the strategies are shown to improve with the exploited knowledge about the request pattern while the computation effort is also increasing. The results give an overview of performance tradeoffs in the whole relevant range for web caching with Zipf request pattern. In a second part, we study a combined approach of the optimum strategy for a limited look-ahead with LRU, LFU or other non-predictive methods. We evaluate the hit rate gain depending on the extent of the look-ahead for request traces and for the independent reference model (IRM) via simulation and derive an analytic confirmation of the observed behaviour. It is shown that caching for video streaming can benefit from the proposed look-ahead technique, when replacement decisions can be partly revised due to new requests being encountered during long lasting content updates.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"67 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":"128861098","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.2018.8362809
Meng Zhang, Jianwei Huang, Rui Zhang
Wireless power transfer (WPT) technology enables a cost-effective and sustainable energy supply in wireless networks, where energy users (EUs) can remotely harvest energy from the wireless signal transmitted by energy transmitters (ETs). However, the broadcast nature of wireless signal makes wireless power a non-excludable public good, which renders the traditional market mechanisms inefficient due to the possibility of the free-riders. In this study, we formulate the transmit power provision problem in a single-channel WPT network as a public good provision problem, aiming to maximize the social welfare of all the ET and EUs considering their private information and selfish behaviors. The considered problem also brings both economic and technical challenges in ensuring voluntary participation and distributed algorithm design. To this end, we propose a two- phase all-or-none procedure involving a low-complexity Power And Taxation (PAT) Nash mechanism, which ensures voluntary participation, incentive compatibility, and budget balance, and yields the socially optimal transmit power at all Nash equilibria. We further propose a distributed D-PAT Algorithm and prove its convergence by exploiting the connection between the structure of Nash equilibria and that of the optimal solutions to a related optimization problem. Finally, our simulation results validate the PAT Mechanism and the practical algorithm. We show that our design can significantly improve the social welfare compared to the benchmark market mechanism, especially when there are many and relatively comparable EUs.
{"title":"Wireless power provision as a public good","authors":"Meng Zhang, Jianwei Huang, Rui Zhang","doi":"10.23919/WIOPT.2018.8362809","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362809","url":null,"abstract":"Wireless power transfer (WPT) technology enables a cost-effective and sustainable energy supply in wireless networks, where energy users (EUs) can remotely harvest energy from the wireless signal transmitted by energy transmitters (ETs). However, the broadcast nature of wireless signal makes wireless power a non-excludable public good, which renders the traditional market mechanisms inefficient due to the possibility of the free-riders. In this study, we formulate the transmit power provision problem in a single-channel WPT network as a public good provision problem, aiming to maximize the social welfare of all the ET and EUs considering their private information and selfish behaviors. The considered problem also brings both economic and technical challenges in ensuring voluntary participation and distributed algorithm design. To this end, we propose a two- phase all-or-none procedure involving a low-complexity Power And Taxation (PAT) Nash mechanism, which ensures voluntary participation, incentive compatibility, and budget balance, and yields the socially optimal transmit power at all Nash equilibria. We further propose a distributed D-PAT Algorithm and prove its convergence by exploiting the connection between the structure of Nash equilibria and that of the optimal solutions to a related optimization problem. Finally, our simulation results validate the PAT Mechanism and the practical algorithm. We show that our design can significantly improve the social welfare compared to the benchmark market mechanism, especially when there are many and relatively comparable EUs.","PeriodicalId":231395,"journal":{"name":"2018 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)","volume":"3 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":"133382627","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.2018.8362857
K. P. Naveen, R. Sundaresan
We consider a recently proposed double-auction mechanism for mobile data-offloading. Network operators (users) derive benefit from offloading their traffic to third party WiFi or femtocell network (link-supplier). A link-supplier experiences costs for the additional capacity that he provides. Users and link-supplier (collectively referred to as agents) have their utilities and cost function as private knowledge. A system-designer decomposes the problem into a network problem (with surrogate utilities and surrogate cost functions) and agent problems (one per agent). The surrogate utilities and cost functions are modulated by the agents' bids. Agents' payoffs and costs are then determined by the allocations and prices set by the system designer. So long as the agents do not anticipate the effect of their actions, a competitive equilibrium exists as a solution to the network and agent problems, and this equilibrium optimizes the system utility. This work shows that when the agents are strategic (price-anticipating), the presence of strategic supplying agents drives the system to an undesirable equilibrium with zero participation. This is in stark contrast to the setting when link-suppliers are not strategic where the efficiency loss is at most 34%. The paper then proposes a Stackelberg game modification to alleviate the efficiency loss problem. The system designer first announces the allocation and payment functions. He then invites the supplying agents to announce their bids. He then invites the users to respond to the suppliers' bids. The resulting efficiency loss is characterized in terms of the suppliers' cost functions.
{"title":"A double-auction mechanism for mobile data-offloading markets with strategic agents","authors":"K. P. Naveen, R. Sundaresan","doi":"10.23919/WIOPT.2018.8362857","DOIUrl":"https://doi.org/10.23919/WIOPT.2018.8362857","url":null,"abstract":"We consider a recently proposed double-auction mechanism for mobile data-offloading. Network operators (users) derive benefit from offloading their traffic to third party WiFi or femtocell network (link-supplier). A link-supplier experiences costs for the additional capacity that he provides. Users and link-supplier (collectively referred to as agents) have their utilities and cost function as private knowledge. A system-designer decomposes the problem into a network problem (with surrogate utilities and surrogate cost functions) and agent problems (one per agent). The surrogate utilities and cost functions are modulated by the agents' bids. Agents' payoffs and costs are then determined by the allocations and prices set by the system designer. So long as the agents do not anticipate the effect of their actions, a competitive equilibrium exists as a solution to the network and agent problems, and this equilibrium optimizes the system utility. This work shows that when the agents are strategic (price-anticipating), the presence of strategic supplying agents drives the system to an undesirable equilibrium with zero participation. This is in stark contrast to the setting when link-suppliers are not strategic where the efficiency loss is at most 34%. The paper then proposes a Stackelberg game modification to alleviate the efficiency loss problem. The system designer first announces the allocation and payment functions. He then invites the supplying agents to announce their bids. He then invites the users to respond to the suppliers' bids. The resulting efficiency loss is characterized in terms of the suppliers' cost functions.","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":"130049256","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.2018.8362813
Bin Li, Bo Ji, Jia Liu
With the rapid growth of Internet of Things (IoT) applications in recent years, there is a strong need for wireless uplink scheduling algorithms that determine when and which subset of a large number of users should transmit to the central controller. Different from the downlink case, the central controller in the uplink scenario typically has very limited information about the users. On the other hand, collecting all such information from a large number of users typically incurs a prohibitively high communication overhead. This motivates us to investigate the development of an efficient and low-overhead uplink scheduling algorithm that is suitable for large-scale IoT applications with limited amount of coordination from the central controller. Specifically, we first characterize a capacity outer bound subject to the sampling constraint where only a small subset of users are allowed to use control channels for system state reporting and wireless channel probing. Next, we relax the sampling constraint and propose a joint sampling and transmission algorithm, which utilizes full knowledge of channel state distributions and instantaneous queue lengths to achieve the capacity outer bound. The insights obtained from this capacity-achieving algorithm allow us to develop an efficient and low-overhead scheduling algorithm that can strictly satisfy the sampling constraint with asymptotically diminishing throughput loss. Moreover, the throughput performance of our proposed algorithm is independent of the number of users, a highly desirable property in large-scale IoT systems. Finally, we perform extensive simulations to validate our theoretical results.
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