Publications (120)74.47 Total impact
- [Show abstract] [Hide abstract] ABSTRACT: Advance reservation is a fundamental paradigm for resource allocation. It is employed in various economic sectors, including cloud computing and communication networks. Although advance reservations are widespread, little is known about the strategic behavior of users facing the decision whether to reserve a resource in advance or not. In this article, we present a game-theoretic framework, called advance reservation (AR) games, to analyze this strategic behavior. We use AR games to analyze the impact of pricing, charging, and information sharing policies on the economic equilibria of the system and on its dynamic behavior. The analysis yields several insights on how a service provider should design a system that supports advance reservations.
- [Show abstract] [Hide abstract] ABSTRACT: Information about queue length is an important parameter for customers who face the decision whether to join a queue or not. In this paper, we study how optimal information disclosure policies can be used by a service provider of an queue to increase its revenue. Our main contribution is showing that the intuitive policy of informing customers about the current queue length when it is short and hiding this information when it is long is never optimal.
- [Show abstract] [Hide abstract] ABSTRACT: We explore and demonstrate the feasibility of implementing distributed solutions for advance reservation of network resources. We introduce a new distributed, distance-vector algorithm, called Distributed Advance Reservation (DAR), that provably returns the earliest time possible for setting up a connection between any two nodes. Our main findings are the following: (i) we prove that widest path routing and path switching (i.e, allowing a connection to switch between different paths) are necessary to guarantee earliest scheduling; (ii) we propose and analyze a novel approach for loop-free distributed widest path routing, leveraging the recently proposed DIV framework. Our routing results directly extend to on-demand and inter-domain QoS routing problems.
- [Show abstract] [Hide abstract] ABSTRACT: With the emergence of connected and autonomous vehicles, sensors are increasingly deployed within cars to support new functionalities. Traffic generated by these sensors congest traditional intra-car networks, such as CAN buses. Furthermore, the large amount of wires needed to connect sensors makes it harder to design cars in a modular way. To alleviate these limitations, we propose, simulate, and implement a hybrid wired/wireless architecture, in which each node is connected to either a wired interface or a wireless interface or both. Specifically, we propose a new protocol, called Hybrid-Backpressure Collection Protocol (Hybrid-BCP), to efficiently collect data from sensors in intra-car networks. Hybrid-BCP is backward-compatible with the CAN bus technology, and builds on the BCP protocol, designed for wireless sensor networks. Hybrid-BCP achieves high throughput and shows resilience to dynamic network conditions, including adversarial interferences. Our testbed implementation, based on CAN and ZigBee transceivers, demonstrates the load balancing and routing functionalities of Hybrid-BCP and its resilience to DoS attacks. We further provide simulation results, obtained with the ns-3 simulator and based on real intra-car RSSI traces, that compare between the performance of Hybrid-BCP and a tree-based collection protocol. Notably, the simulations show that Hybrid-BCP can achieve the same performance as the tree-based protocol while reducing the radio transmission power by a factor of 10.
- [Show abstract] [Hide abstract] ABSTRACT: Device-to-Device (D2D) communication that enables nearby mobiles to directly communicate one with another is a new paradigm aimed at increasing the capacity of next-generation wireless networks. The coexistence of D2D and cellular communication in the same spectrum poses new challenges for resource allocations and interference management in a large-scale wireless system where each mobile strategically selects its mode of communications. This paper formulates a game-theoretic framework to capture the distributed strategic behavior of a large population of mobiles in selecting their mode of communications. In particular, we investigate the impact of Queue State Information (QSI) of the base station (BS) on the mobile decisions, and we show that the common knowledge of QSI can induce bad quality of service for standard cellular traffic, when the capacity of the base station is below a certain threshold. This paradox will be used to guide the design of optimal learning and scheduling algorithms for the coexisting D2D communication networks.
- [Show abstract] [Hide abstract] ABSTRACT: Modern vehicles incorporate dozens of sensors to provide vital sensor data to electronic control units, typically through physical wires, which increase the weight, maintenance, and cost of cars. Wireless sensor networks have been contemplated for replacing the current physical wires with wireless links, although existing networks are all single-hop, presumably because cars are small enough to be covered by lowpower communication, and multihop networking requires organizational overhead. In contradiction with previous works, we experimentally investigate the use of multihop wireless communication to support intra-car sensor networking. Extensive tests, run under various vehicular environments, indicate the potential for significant reliability, robustness, and energy usage improvements over existing single-hop approaches. Our implementation is based on the Collection Tree Protocol, a state-of-the-art multihop data collection protocol.
- [Show abstract] [Hide abstract] ABSTRACT: Advance reservation (AR) services form a pillar of many branches of the economy, e.g., transportation, lodging, dining, and health care. There has also been increased interest in applying AR in cloud computing systems . For instance, Moab Workload Manager  and IBM Platform Computing Solutions  support AR. In both of these pack- Ages, an administrator can decide whether or not to enable AR and define an AR pricing scheme. In most systems supporting AR, customers can choose whether making AR or not. Since the payoff of each customer is affected by decisions of other customers, it is natural to analyze the behavior of such systems as strategic games. In this work, we study a strategic non-cooperative game, referred to as an advance reservation game. In this game, players (customers) can reserve future resources in advance for a fixed reservation fee C. We consider a slotted loss system with N servers where customers are not flexible, i.e., they leave the system if they cannot be served at their desired time slots. Customers are not informed of the state of the system (i.e., the number of unreserved servers) prior to attempting a reservation. Thus, a customer opting not to make a reservation lowers its chance of finding a server available at the desired time. The number of customers in each slot is an i.i.d. Poisson random variable with parameter . Customers have different lead times, where the lead time of a customer is defined as the time elapsing between its arrival and the slot starting time. Each customer only knows its own lead time. However, all lead times are derived from the same continuous distribution known by both the provider and the customers. In , we derive the equilibria structure of AR games. We show that for any C > 0, only two types of equilibria are possible. In the first type, none of the customers, regardless of their lead times, makes AR (non-make-AR equilibrium). In the second type, only customers with lead time greater than some threshold make AR (threshold equilibrium). Furthermore, we establish the existence of three different ranges of fees, such that if C falls in the first range only threshold equilibria exist, in the second range both threshold equilibria and a none-make-AR equilibrium exist, and in the third range only a none-make-AR equilibrium exists. In many cases, the fee C that maximizes the provider's profit lies in the second range. However, setting up a fee in that range carries also the risk of zero profit for the provider. Therefore, in order to properly set the AR fee, the provider should consider both the fee yielding the maximum possible profit and the fee yielding the maximum guaranteed profit. A guaranteed profit can be only achieved using fees falling within the first range. In this work, we introduce the concept of price of conservatism (PoC), which corresponds to the ratio of the maximum possible profit to the maximum guar- Anteed profit, and analyze it in different regimes. A greater PoC indicates greater potential profit loss if the provider opts to be conservative. First, we analyze a single-server regime, where we prove that for any fee the equilibrium is unique (the second range collapses in that case). Hence, PoC = 1 and the provider experiences no loss. Next, we analyze a many-server regime where λ = αN and N → 1. We distinguish between the cases of overloaded and underloaded systems (i.e., α > 1 and α < 1 respectively). For the overloaded case, we show that PoC = α=(α-1). Hence, the price of conservatism increases in an unbounded fashion as α approaches one from above. Finally, for the underloaded case, we show that both the maximum and guaranteed profits converge to zero.
- [Show abstract] [Hide abstract] ABSTRACT: We introduce a private commons model that consists of network providers who serve a fixed primary demand and strategically price to improve their revenues from an additional secondary demand. For general forms of secondary demand, we establish the existence and uniqueness of two characteristic prices: the break-even price and the market sharing price. We show that the market sharing price is always greater than the break-even price, leading to a price interval in which a provider is both profitable and willing to share the demand. Making use of this result, we give insight into the nature of market outcomes.
- [Show abstract] [Hide abstract] ABSTRACT: This paper characterizes the outcomes of secondary spectrum markets when multiple providers compete for secondary demand. We study a competition model in which each provider aims to enhance its revenue by opportunistically serving a price-dependent secondary demand, while also serving dedicated primary demand. We consider two methodologies for sharing spectrum between primary and secondary demand: In coordinated access, spectrum providers have the option to decline a secondary access request if that helps enhance their revenue. We explicitly characterize a break-even price such that profitability of secondary access provision is guaranteed if secondary access is priced above the break-even price, regardless of the volume of secondary demand. Consequently, we establish that competition among providers that employ optimal coordinated access leads to a price war, as a result of which the provider with the lowest break-even price captures the entire market. This result holds for arbitrary secondary demand functions. In uncoordinated access, primary and secondary users share spectrum on equal basis, akin to ISM bands. Under this policy, we characterize a market sharing price that determines a provider's willingness to share the market. We show an instance where the market sharing price is strictly greater than the break-even price, indicating that market equilibrium in an uncoordinated access setting can be fundamentally different as it opens up the possibility of providers sharing the market at higher prices.
- [Show abstract] [Hide abstract] ABSTRACT: We introduce a theoretical framework to formally analyze the vulnerability of IEEE 802.11 rate adaptation algorithms (RAAs) to selective jamming attacks, and to develop countermeasures providing provable performance guarantees. Thus, we propose a new metric called Rate of Jamming (RoJRoJ), wherein a low RoJRoJ implies that an RAA is highly vulnerable to jamming attacks, while a high RoJRoJ implies that the RAA is resilient. We prove that several state-of-the-art RAAs, such as ARF and SampleRate, have a low RoJRoJ (i.e., 10%10% or lower). Next, we propose a robust RAA, called Randomized ARF (RARF). Using tools from renewal theory, we derive a closed-form lower bound on the RoJRoJ of RARF. We validate our theoretical analysis using ns-3 simulations and show that the minimum jamming rate required against RARF is about 33%33% (i.e., at least three times higher than the RoJRoJ of other RAAs).
- [Show abstract] [Hide abstract] ABSTRACT: We introduce an economic model for private commons that consists of network providers serving a fixed primary demand and making strategic pricing decisions to improve their revenues by providing service to a secondary demand. For general forms of secondary demand, we establish the existence and uniqueness of two critical prices for each provider: the break-even price and the market sharing price. The prior determines service profitability while the latter determines a provider's willingness to share the market. We further show that the market sharing price is always greater than the break-even price, leading to a price interval in which a provider is both profitable and willing to share the market. Making use of these results, we shed insight into the nature of market outcomes (Nash equilibria) when two providers compete to attract secondary demand: (i) if the market sharing intervals of the two providers overlap, then the providers end up sharing the market; (ii) else, the provider with the lower break-even price captures the entire market as the result of a price war.
Conference Paper: Game-theoretic analysis of advance reservation services[Show abstract] [Hide abstract] ABSTRACT: In many services, such as cloud computing, customers have the option to make reservations in advance. However, little is known about the strategic behavior of customers in such systems. In this paper, we use game theory to analyze several models of time-slotted systems in which customers can choose whether or not making an advance reservation of server resources in future time slots. Since neither the provider nor the customers know in advance how many customers will request service in a given slot, the models are analyzed using Poisson games, with decisions made based on statistical information. The games differ in their payment mechanisms, and the main objective is to find which mechanism yields the highest average profit for the provider. Our analysis shows that the highest profit is achieved when advance reservation fees are charged only from customers that are granted service. Furthermore, informing customers about the availability of free servers prior to their decisions do not affect the provider's profit in that case.
- [Show abstract] [Hide abstract] ABSTRACT: New regulations grant network service providers with the right to lease their spectrum to short-term leased secondary users (SUs) for opportunistic usage. In this work, we tackle the challenge of determining admission control and pricing policies on SUs that guarantee profitability under general secondary demand and general traffic models, and accurately reflect the operation of modern cellular data networks in which resources are shared rather than rigidly partitioned. We first analyze the joint problem of bandwidth allocation and admission control of elastic secondary users. We assume Poisson session arrivals, where each session is composed of arbitrarily distributed, and possibly correlated, on and off periods. Under balanced bandwidth allocation, we show that the steady state distribution of the number of active users in the network is insensitive to traffic characteristics beyond their means. This result holds for arbitrary occupancy-based admission control policies on SUs. Next, we prove that the optimal occupancy-based admission control policy is of threshold type, which means that secondary user arrivals are accepted when the total number of active users in the network is below a certain threshold; otherwise, they are rejected. Finally, we identify a price,referred to as the break-even price, and an admission control policy which, together, ensure profitability for any price greater than the break-even price, irrespective of the shape of the secondary demand function.
Conference Paper: On the channel-sensitive delay behavior of LIFO-backpressure[Show abstract] [Hide abstract] ABSTRACT: In this paper, we study the delay performance of backpressure routing algorithms using LIFO schedulers (LIFO-backpressure). We uncover a surprising behavior in which, under certain channel conditions, the average delay of packets decreases as the traffic load in the network increases. We propose and analyze a queueing-theoretic model under which the scheduler can transmit packets only if the queue length (i.e., the number of packets in the queue) meets or exceeds a threshold, and we show that the model analytically bears out the observed phenomenon. Using matrix geometric methods, we derive a numerical solution for the average packet delay in the general case, and, using z-transform techniques, we further provide closed-form solutions for the average delay in special cases. Our analysis indicates that when the threshold is fixed (as may happen under lossless channel conditions), the average delay increases with increasing traffic load, as expected. On the other hand, when the threshold fluctuates (as may happen under changing, lossy channel conditions), the average delay may decrease, sometimes substantially, with the traffic load. We corroborate these findings with TOSSIM simulations using real channel traces and run on different types of networks.
- [Show abstract] [Hide abstract] ABSTRACT: Several collection protocols have been developed to achieve efﬁcient gathering of data in Wireless Sensor Networks (WSN) including intra-car WSN. Though there exist WSN tools capable of controlling, monitoring, and displaying sensor data, there is still a need for a general benchmarking tool capable of visualizing, evaluating, and comparing the network layer performance of these protocols. In an effort to ﬁll this gap, we present TeaCP, a prototype Toolkit for the evaluation and analysis of Collection Protocols in both simulation and experimental environments. Through simulation of an intra-car WSN and real lab experiments, we demonstrate the functionality of TeaCP for comparing the performance of two prominent collection protocols, the Collection Tree Protocol (CTP) and the Backpressure Collection Protocol (BCP).
Conference Paper: Intra-Car Wireless Sensors Data Collection: A Multi-Hop Approach[Show abstract] [Hide abstract] ABSTRACT: We experimentally investigate the benefits of multihop networking for intra-car data aggregation under the current state-of-the-art Collection Tree Protocol (CTP). We show how this protocol actively adjusts collection routes according to channel dynamics in various practical car environments, resulting in performance gains over single-hop aggregation. Throughout our experiments, we target traditional performance metrics such as delivery rate, number of transmissions per packet, and delay, and our results confirm, both qualitatively and quantitatively, that multi-hop communication can provide a reliable and robust approach for data collection within a car.
- [Show abstract] [Hide abstract] ABSTRACT: Few technical details are available about the various sensors embedded in modern smartphones, and what details are available can be hard to assemble and interpret by the broader technical community that uses these devices. Since the physical and electromagnetic aspects of the sensors' operation can significantly affect the analysis and use of their data, it is essential for those who rely on these data to understand these details. As such, the authors provide a simplified and yet technically precise explanation of some of the sensors found on the Motorola Droid, which are representative of sensors found in most smartphones. The authors specifically explain its proximity sensor, Hall effect magnetometer, capacitive accelerometer, orientation sensor, and light sensor. Each sensor is described using illustrations and experiments that are provided to demonstrate some unexpected behaviors.
- [Show abstract] [Hide abstract] ABSTRACT: Ongoing regulatory reforms have led to several novel spectrum sharing models under the general umbrella of dynamic spectrum sharing. The private commons model introduced by FCC in 2004 allows spectrum licensees to provide secondary access to spectrum on an opportunistic basis while retaining ownership. Since wireless communication systems are typically overprovisioned in order to deliver service-level guarantees to (primary) users under short-term load variations, this model bears significant potential by facilitating utilization of temporal and spatial surplus of capacity through serving secondary users at possibly different service levels. A potential barrier to adoption of the private commons model is the uncertainty about secondary price–demand relationship which is difficult to predict in an emerging market: A selected price for secondary access may be profitable for some values of secondary demand but not for others, leading to a profound uncertainty about ultimate benefit of spectrum sharing. This paper aims to eliminate such an uncertainty by devising concrete guidelines and methods for profitability. The paper establishes that the price of secondary spectrum access can be chosen to guarantee profitability for any value of secondary demand: It is shown that for both the coordinated and uncoordinated commons regimes a profitable price should exceed a threshold value, which can be calculated. Hence profitability of private commons is insensitive to the demand function. This observation has two complementary interpretations: From a business perspective it provides a constructive approach to profitability; and from a regulatory perspective it provides reassurance that private commons is a healthy model. The paper also leverages the insensitivity property and outlines a technique to further enhance revenue via iterative spectrum offerings.
Boston, Massachusetts, United States
- Department of Electrical and Computer Engineering
University of California, Berkeley
Berkeley, California, United States
- Department of Electrical Engineering and Computer Sciences
Massachusetts Institute of Technology
Cambridge, Massachusetts, United States
- Department of Physics
Technion - Israel Institute of Technology
H̱efa, Haifa District, Israel
- Electrical Engineering Group