{"title":"Store or sell? A threshold price policy for revenue maximization in windfarms with on-site storage","authors":"Zamiyad Dar, K. Kar, J. Chow","doi":"10.1109/CISS.2016.7460491","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460491","url":null,"abstract":"We consider the problem of maximizing the revenue of a windfarm with on-site storage, and propose and analyze a scheme for a windfarm to store or sell energy based on a threshold price. The threshold price is calculated based on long-term distributions of the electricity price and wind power generation processes, and is chosen so as to balance the energy flows in and out of the storage-equipped windfarm. We apply our method on real time data from a windfarm in New York, along with real time electricity prices from NYISO for the same region and time period. Comparing it with the optimal policy that has knowledge of the future, we observe that the revenue obtained by our threshold policy increases as the storage capacity is increased, and is approximately 90% of the maximum attainable revenue at a storage capacity of 10-15 times the power rating.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115475067","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}
{"title":"Battle of opinions over evolving social networks","authors":"Irem Koprulu, Yoora Kim, N. Shroff","doi":"10.1109/CISS.2016.7460472","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460472","url":null,"abstract":"Social networking platforms are responsible for the discussion and formation of opinions in diverse areas including, but not limited to, political discourse, market trends, news and social movements. Often, these opinions are of a competing nature, e.g., radical vs. peaceful ideology, one technology vs. another. We study the battle of such competing opinions over evolving social networks. The novelty of our model is that it captures the exposure and adoption dynamics of opinions that account for the preferential and random nature of exposure as well as the persuasion power of different opinions. We provide a complete characterization of the mean opinion dynamics over time as a function of the initial adoption as well as the particular exposure and adoption dynamics. Our analysis, supported by case studies, reveals the key metrics that govern the spread of opinions and establishes the means to engineer the desired impact of an opinion in the presence of other competing opinions.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126782719","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}
Ahmed A. Alabdel Abass, M. Hajimirsadeghi, N. Mandayam, Z. Gajic
{"title":"Evolutionary game theoretic analysis of distributed denial of service attacks in a wireless network","authors":"Ahmed A. Alabdel Abass, M. Hajimirsadeghi, N. Mandayam, Z. Gajic","doi":"10.1109/CISS.2016.7460473","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460473","url":null,"abstract":"We consider a wireless network of M users connected to an access point in the presence of N jammers whose purpose is to deny or degrade the performance of the users by injecting interference. Using the achieved signal to inference plus noise ratio (SINR) as the performance metric, we study the dynamics of such a distributed denial of service attack (DDoA) by using Evolutionary Game Theory (EGT). Specifically, we consider a cooperative network model, where the M users (and N jammers) can collectively enhance their achieved SINR (degrade the user SINR). We model the strategic transmission decisions of the users (and the jammers) using simple random access techniques where the users (and jammers) decide to transmit or not with a transmission probability, taking into account their energy costs. Using the replicator dynamics (RD), we characterize the evolutionary stable strategies (ESS's) of the game and observe that the resulting transmission probabilities turn out to be either 0 or 1. Further, given a network (channel) setting, we show using a phase portrait of the replicator dynamics how the ESS strategies evolve for different cooperation levels of the users and jammers populations. We also provide insights into resulting ESS strategies as a function of the number of users and jammers, and their channel qualities.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115368185","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}
C. Tan, Pei-Duo Yu, Chun-Kiu Lai, Wenyi Zhang, H. Fu
{"title":"Optimal detection of influential spreaders in online social networks","authors":"C. Tan, Pei-Duo Yu, Chun-Kiu Lai, Wenyi Zhang, H. Fu","doi":"10.1109/CISS.2016.7460492","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460492","url":null,"abstract":"The wide availability of digital data in online social networks such as the Facebook offers an interesting question on finding the influential users based on the user interaction over time. An example is the clicking of the Facebook “Like” button to endorse a digital object (e.g., a post or picture) posted by other user. This online interaction activity connects users sharing similar opinions or disposition and spreads their influence. In this paper, we study the estimation problem of finding a small number of users in the online social network who are influential in maximizing the reach of a digital message when it originates from them. The digital interaction in the online social network can be modeled using an interaction graph, e.g., associate users through the past record of snapshot observations of Like's activity in Facebook. We propose a network centrality approach in which we first use graph convexity to characterize the relative influential level of users on the interaction graph. We then propose a message passing algorithm to rank these users in order to identify the influential spreaders who play a forward-engineering role in catalyzing the spread of a new message. A useful application is to schedule a cascade of endorsement of a digital marketing message or for a business entity with a Facebook presence to find a number of Facebook users to spread the word of new commercial products. Lastly, we describe the performance of our algorithm using a synthetic dataset.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115829993","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}
Benjamin Peiffer, R. Mudumbai, A. Kruger, Amy Kumar, S. Dasgupta
{"title":"Experimental demonstration of a distributed antenna array pre-synchronized for retrodirective transmission","authors":"Benjamin Peiffer, R. Mudumbai, A. Kruger, Amy Kumar, S. Dasgupta","doi":"10.1109/CISS.2016.7460546","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460546","url":null,"abstract":"We describe the key ideas behind our implementation of a distributed antenna array fully pre-synchronized for retrodirective transmission to an external receiver. In our implementation, a number of wireless transceivers in a network use a sequence of simple in-band wireless message exchanges to calibrate themselves so that these transceivers can obtain their channel gains to an external receiver using reciprocity simply by observing a single incoming transmission from that receiver without any channel feedback or other cooperation from the receiver. Some notable features of our implementation are as follows: (a) it automatically calibrates and corrects for unknown channel gains, oscillator offsets and drifts between the array nodes as well as the effect of non-reciprocal RF hardware; (b) it is fully wireless and endogenous i.e., does not use any wired backhaul connections or side channels including GPS; and (c) it uses simple signal processing on a standard and widely available software-defined radio platform based on off-the-shelf hardware and open-source software. Also, to the best of our knowledge, this is the first ever demonstration of a pre-synchronized distributed array, and thus our implementation serves as a proof-of-concept and allows for the development of more advanced distributed array techniques building on this capability.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125178033","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}
{"title":"Spatial-temporal routing for supporting end-to-end hard deadlines in multi-hop networks","authors":"Xin Liu, Lei Ying","doi":"10.1109/CISS.2016.7460512","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460512","url":null,"abstract":"We consider the problem of routing packets with end-to-end hard deadlines in communication networks. The problem is challenging due to the complex spatial-temporal correlation among flows with different deadlines. To tackle this challenging problem, we introduce the concepts of virtual links/routes to incorporate end-to-end deadline constraints into routing and propose a novel virtual queue architecture to guide the spatial-temporal routing which specifies where and when a packet should be routed. The proposed policy can support any periodic constant traffic within the network throughput region. Our simulations further show that the policy outperforms traditional policies such as backpressure and earliest-deadline-first (EDF) for general traffic flows.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"55 1-2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126960342","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}
Debankur Mukherjee, S. Borst, J. V. Leeuwaarden, P. Whiting
{"title":"Efficient load balancing in large-scale systems","authors":"Debankur Mukherjee, S. Borst, J. V. Leeuwaarden, P. Whiting","doi":"10.1109/CISS.2016.7460533","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460533","url":null,"abstract":"We consider a system of N identical parallel server pools and a single dispatcher where tasks arrive as a Poisson process. Arriving tasks cannot be queued, and must immediately be assigned to one of the server pools to start execution. The execution times are assumed to be exponentially distributed, and do not depend on the number of tasks contending for service. However, the experienced performance (e.g. in terms of received throughput or packet-level delay) does degrade with an increasing number of concurrent tasks at the same server pool. In order to optimize the performance, the dispatcher therefore aims to evenly distribute the tasks across the various server pools, using either a power-of-d or a threshold-based load balancing scheme. In the power-of-d scheme, an arriving task is assigned to the server pool with the minimum number of active tasks among d(N) randomly selected server pools (1 ≤ d(N) ≤ N). In the threshold-based scheme, an incoming task is dispatched to an arbitrary server pool with fewer than L active tasks, if there is any, to an arbitrary server pool with fewer than H > L tasks otherwise, or to a randomly selected server pool if all server pools have H or more tasks. This scheme can be implemented in a server-driven manner, with O(1) communication overhead per task, as opposed to O(d(N)) in the power-of-d scheme. We derive the fluid-level dynamics for the power-of-d scheme with d(N) → ∞ as N → ∞ and the threshold-based scheme, along with the associated fixed points. As it turns out, the fluid limit for the power-of-d scheme does not depend on the exact growth rate of d(N). We also characterize the diffusion-level behavior of the power-of-d scheme with d(N) ≫ √N log(N), and show that it coincides with that of the threshold-based scheme with suitably selected parameters L and H. In particular, the threshold-based scheme can achieve similar performance as the power-of-d scheme with d(N) ≫ √N log(N), and thus diffusion-level optimality, with only O(1) rather than O(N) communication overhead per task.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121886014","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}
{"title":"The impact of investment on small-cell resource allocation","authors":"Cheng Chen, R. Berry, M. Honig, V. Subramanian","doi":"10.1109/CISS.2016.7460558","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460558","url":null,"abstract":"We consider a heterogeneous wireless network serving two classes of users: mobile and fixed. Mobile users can only associate with macro-cells while fixed users can be served by either macro- or small-cells. Multiple service providers (SPs) can operate in the network and each has the same macro-cell infrastructure. In contrast, each SP determines a small-cell deployment density by its investment. Each SP is given a fixed total bandwidth, which is split between macro- and small-cell service, and charges a price per unit rate for each type of service. The objective of each SP is then to select the price, bandwidth split, and investment in small-cells to maximize either revenue or social welfare. We first assume a single SP and characterize the optimal strategies for both revenue and social welfare maximization. The deployment density largely depends on the per unit deployment cost of small-cells. We then consider a binary investment game in which each SP has the option of investing in a small-cell network with fixed deployment density, and show that equilibria exist in which one, none, or both SPs invest. In most cases, the pure strategy equilibria are not socially optimal. In addition, there exists asymmetric equilibrium where one SP invests in small-cells while the other doesn't. Numerical results are presented that illustrate the effect of deployment cost on small-cell investment.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128181767","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}
{"title":"Background traffic optimization for meeting deadlines in data center storage","authors":"Shijing Li, Tian Lan, Moo-Ryong Ra, R. Panta","doi":"10.1109/CISS.2016.7460531","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460531","url":null,"abstract":"Background traffic, such as repair, rebalance, backup and recovery traffic, often has large volume and consumes significant network resources in cloud storage systems. While having each application independently schedule its own background traffic can easily generate interference among data flows, causing violation of desired QoS requirements (e.g., latency and deadline), heuristic scheduling algorithms like Earliest-Deadline-First and First-In-First-Out are not able to take into account data center constraints such network topology or data chunk placement, thus resulting in unsatisfactory performance. In this paper, we propose a new algorithm, Linear Programming for Selected Tasks (LPST), which coordinate background traffic of different jobs to meet traffic deadline and optimize system throughput. In particular, our goal is to maximize the number of background traffic flows that meet their target deadlines under bandwidth constraints in data center storage systems. Using realistic traffic trace, our simulation results show that the proposed algorithm significantly improves task processing time and the probability of meeting deadlines.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132014799","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}
{"title":"Sufficient conditions for stable recovery of sparse autoregressive models","authors":"A. Kazemipour, B. Babadi, Min Wu","doi":"10.1109/CISS.2016.7460535","DOIUrl":"https://doi.org/10.1109/CISS.2016.7460535","url":null,"abstract":"We consider the problem of estimating the parameters of autoregressive linear models with subGaussian innovations from limited observations, where the history of the process composes the covariate. We analyze the performance of lasso type and greedy estimators and characterize the sampling tradeoffs required for stable recovery in the non-asymptotic regime. Our results extend those of compressed sensing for linear models with i.i.d. covariates to autoregressive processes with highly interdependent covariates. We further provide simulation studies as well as application to financial data which confirm our theoretical predictions.","PeriodicalId":346776,"journal":{"name":"2016 Annual Conference on Information Science and Systems (CISS)","volume":"30 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132463390","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}