Showing papers by "Nitin H. Vaidya published in 2011"
10 Apr 2011
TL;DR: This paper model the radio spectrum allocation problem as a sealed-bid reserve auction, and proposes SMALL, which is a Strategy-proof Mechanism for radio spectrum ALLocation, and extends it to adapt to multi-radio spectrum buyers, which can bid for more than one radio.
Abstract: With the growing deployment of wireless communication technologies, radio spectrum is becoming a scarce resource. Thus mechanisms to efficiently allocate the available spectrum are of interest. In this paper, we model the radio spectrum allocation problem as a sealed-bid reserve auction, and propose SMALL, which is a Strategy-proof Mechanism for radio spectrum ALLocation. Furthermore, we extend SMALL to adapt to multi-radio spectrum buyers, which can bid for more than one radio.
87 citations
10 Apr 2011
TL;DR: This paper model the problem of adaptive-width channel allocation as a strategic game, and shows the existence of Nash equilibrium (NE), and proposes a charging scheme to influence the players' behavior, by which the system is guaranteed to converge to a Dominant Strategy Equilibrium (DSE), a solution concept that gives participants much stronger incentives.
Abstract: Due to the limitation of radio spectrum resource and fast growing of wireless applications, careful channel allocation is highly needed to mitigate the performance degradation of wireless networks because of interference among different users. While most of the existing works consider allocating fixed-width channels, combining contiguous channels may provide an alternative way to better utilize the available channels. In this paper, we study the problem of adaptive-width channel allocation from a game-theoretic point of view, in which the nodes are rational and always pursue their own objectives. We first model the problem as a strategic game, and show the existence of Nash equilibrium (NE), when there is no exogenous factor to influence players' behavior. We further propose a charging scheme to influence the players' behavior, by which the system is guaranteed to converge to a Dominant Strategy Equilibrium (DSE), a solution concept that gives participants much stronger incentives. We show that, when the system converges to a DSE, it also achieves global optimality, in terms of system-wide throughput without starvation. Numerical results verify that with our charging scheme, the system-wide throughput obtained is higher as compared to the throughput obtained when system is in NE.
41 citations
06 Jun 2011
TL;DR: In this article, an efficient deterministic algorithm for consensus in presence of Byzantine failures is presented, which achieves consensus on an L-bit value with communication complexity O(nL + n4L 0.5 + n6) bits.
Abstract: In this paper, we present an efficient deterministic algorithm for consensus in presence of Byzantine failures. Our algorithm achieves consensus on an L-bit value with communication complexity O(nL + n4L0.5 + n6) bits, in a network consisting of n processors with up to t Byzantine failures, such that t
31 citations
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TL;DR: In this article, the authors investigate the multi-valued Byzantine consensus problem and introduce two algorithms: the first achieves traditional validity requirement for consensus, and the second one achieves a stronger "q-validity" requirement.
Abstract: In this report, we investigate the multi-valued Byzantine consensus problem. We introduce two algorithms: the first one achieves traditional validity requirement for consensus, and the second one achieves a stronger "q-validity" requirement. Both algorithms are more efficient than the ones introduces in our recent PODC 2011 paper titled "Error-Free Multi-Valued Consensus with Byzantine Failures".
30 citations
10 Apr 2011
TL;DR: It is shown that CSMA can achieve an arbitrary fraction of the capacity region if certain access probabilities are set appropriately and the perturbation theory of Markov chains is used.
Abstract: Recently, it has been shown that a simple, distributed CSMA algorithm can achieve throughput-optimality. However, the optimality is established under the ideal carrier sensing assumption, i.e., each link can precisely sense the presence of other active links in its neighborhood. This paper, in contrast, investigates the achievable throughput of the CSMA algorithm under imperfect carrier sensing. The main result is that CSMA can achieve an arbitrary fraction of the capacity region if certain access probabilities are set appropriately. To establish this result, we use the perturbation theory of Markov chains.
25 citations
26 Jun 2011
TL;DR: This paper constructs a static protocol that solves the MEQ problem for n = 3, K = 6, of which the communication cost is strictly lower than the above upper bound (2 log2 6 bits), and is generalized for large values of n and K.
Abstract: In this paper, we study the problem of computing the multiparty equality (MEQ) function: n ≥ 2 nodes, each of which is given an input value from {1,...,K}, determine if their inputs are all identical, under the point-to-point communication model. The MEQ function equals to 1 if and only if all n inputs are identical, and 0 otherwise. The communication complexity of the MEQ problem is defined as the minimum number of bits communicated in the worst case. It is easy to show that (n-1) log2 K bits is an upper bound, by constructing a simple algorithm with that cost. In this paper, we demonstrate that communication cost strictly lower than this upper bound can be achieved. We show this by constructing a static protocol that solves the MEQ problem for n = 3, K = 6, of which the communication cost is strictly lower than the above upper bound (2 log2 6 bits). This result is then generalized for large values of n and K.
19 citations
TL;DR: The proposed multicast protocol builds multicast paths while inviting multicast members, and tries to allocate the same channel to neighboring members in a bottom-up manner, which can improve the performance such as reducing multicast data transmission overhead and delay, while managing a successful delivery ratio.
Abstract: Multicasting is a useful communication method in wireless mesh networks (WMNs). Many applications in WMNs require efficient and reliable multicast communications, i.e., high delivery ratio with low overhead among a group of recipients. In spite of its significance, little work has been done on providing such multicast service in multi-channel WMNs. Traditional multicast protocols for wireless and multi-hop networks tend to assume that all nodes, each of which is equipped with a single interface, collaborate on the same channel. This single-channel assumption is not always true, as WMNs often provide nodes with multiple interfaces to enhance performance. In multi-channel and multi-interface (MCMI) WMNs, the same multicast data must be sent multiple times by a sender node if its neighboring nodes operate on different channels. In this paper, we try to tackle the challenging issue of how to design a multicast protocol more suitable for MCMI WMNs. Our multicast protocol builds multicast paths while inviting multicast members, and tries to allocate the same channel to neighboring members in a bottom-up manner. By unifying fixed channels of one-hop multicast neighbors, the proposed algorithm can improve the performance such as reducing multicast data transmission overhead and delay, while managing a successful delivery ratio. In order to prove such expectation on the performance, we have implemented and evaluated the proposed solution on the real testbed having the maximum 24 nodes, each of which is equipped with two IEEE 802.11a Atheros WLAN cards.
18 citations
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TL;DR: This paper proves convergence of the robustified consensus scheme of e a coefficients of ergodicity approach, a method commonly used for convergence analysis of Markov chains, and suggests that similar convergence should hold under more general conditions as well.
Abstract: In this two-part paper, we consider multicomponent systems in which each component can iteratively exchange information with other components in its neighborhood in order to compute, in a distributed fashion, the average of the components' initial values or some other quantity of interest (i.e., some function of these initial values). In particular, we study an iterative algorithm for computing the average of the initial values of the nodes. In this algorithm, each component maintains two sets of variables that are updated via two identical linear iterations. The average of the initial values of the nodes can be asymptotically computed by each node as the ratio of two of the variables it maintains. In the first part of this paper, we show how the update rules for the two sets of variables can be enhanced so that the algorithm becomes tolerant to communication links that may drop packets, independently among them and independently between different transmission times. In this second part, by rewriting the collective dynamics of both iterations, we show that the resulting system is mathematically equivalent to a finite inhomogenous Markov chain whose transition matrix takes one of finitely many values at each step. Then, by using e a coefficients of ergodicity approach, a method commonly used for convergence analysis of Markov chains, we prove convergence of the robustified consensus scheme. The analysis suggests that similar convergence should hold under more general conditions as well.
15 citations
TL;DR: The focus of this paper is to robustify this double-iteration algorithm against communication link failures by modifying the double- iteration algorithm (by introducing some additional auxiliary variables) and proving that the modified double-Iteration converges almost surely to average consensus.
Abstract: : This two-part paper discusses robustification methodologies for linear-iterative distributed algorithms for consensus and coordination problems in multicomponent systems, in which unreliable communication links may drop packets. We consider a setup where communication links between components can be asymmetric (i.e. component j might be able to send information to component i, but not necessarily vice-versa), so that the information exchange between components in the system is in general described by a directed graph that is assumed to be strongly connected. In the absence of communication link failures, each component i maintains two auxiliary variables and updates each of their values to be a linear combination of their corresponding previous values and the corresponding previous values of neighboring components (i.e., components that send information to node i). By appropriately initializing these two (decoupled) iterations, the system components can asymptotically calculate variables of interest in a distributed fashion; in particular, the average of the initial conditions can be calculated as a function that involves the ratio of these two auxiliary variables. The focus of this paper to robustify this double-iteration algorithm against communication link failures. We achieve this by modifying the double-iteration algorithm (by introducing some additional auxiliary variables) and prove that the modified double-iteration converges almost surely to average consensus. In the first part of the paper, we study the first and second moments of the two iterations, and use them to establish convergence, and illustrate the performance of the algorithm with several numerical examples. In the second part, in order to establish the convergence of the algorithm, we use coefficients of ergodicity commonly used in analyzing inhomogeneous Markov chains.
13 citations
27 Jun 2011
TL;DR: This paper proposes Any-MAC — a generic, low overhead extension that can be applied to any existing asynchronous MAC protocol to enable MAC-layer anycast, and shows that anycast to existing protocols, X-MAC and NPM, uses only simple modification to the base protocols and improves the performance significantly.
Abstract: Delay in a duty-cycled network occurs when the sender waits for its receiver to be awake. Exploiting multiple receivers instead of a single receiver at each hop allows the sender to use the node that wakes up the soonest and so reduce delay. However, current MAC-layer anycast protocols either suffer from high signaling or synchronization overhead and are only appropriate for low duty cycle, low traffic scenarios. In this paper, we propose Any-MAC — a generic, low overhead extension that can be applied to any existing asynchronous MAC protocol to enable MAC-layer anycast. The extensive research in duty-cycle protocols provides us many MAC protocols, each appropriate for a particular network and application scenario. Thus, to construct an anycast solution to reduce delay for a specific network scenario, Any-MAC simply needs to extend the appropriate MAC protocol designed for that scenario. By applying anycast to existing protocols, X-MAC and NPM, we show that Any-MAC uses only simple modification to the base protocols and improves the performance significantly. Our evaluations in ns-2 show that with Any-MAC, both protocols can achieve 30% improvements in delay by exploiting the inherent route level redundancy in the network.
12 citations
10 Apr 2011
TL;DR: The throughput and capacity of agreement are defined, and necessary conditions of achievable agreement throughputs are identified, and an algorithm structure for achieving agreement capacity in general networks is proposed.
Abstract: We consider the problem of maximizing the throughput of Byzantine agreement, when communication links have finite capacity. Byzantine agreement is a classical problem in distributed computing. In existing literature, the communication links are implicitly assumed to have infinite capacity. The problem changes significantly when the capacity of links is finite. We define the throughput and capacity of agreement, and identify necessary conditions of achievable agreement throughputs. We propose an algorithm structure for achieving agreement capacity in general networks. We also introduce capacity achieving algorithms for two classes of networks: (i) arbitrary four-node networks with at most 1 failure; and (ii) symmetric networks of arbitrary size.
27 Jun 2011
TL;DR: This paper proposes a protocol called WiSP (channel Width Selection based on Packet size) to estimate the appropriate channel widths depending on the relative traffic load involving short and long packets in the network, and proposes an algorithm to complement the frame aggregation technique.
Abstract: In this paper, we propose to reduce the effect of rate-independent MAC overheads in random access protocols by partitioning the transmission channel spectrum into a narrow channel and a wide channel. The narrow channel is used for transmitting the short packets (approximately 100 bytes long) and the wide channel is used for transmitting the longer packets. We intend to use multiple radios, one each for the different channel partitions. Narrow width channels have a reduced capacity, which lowers the maximum transmission rate achievable on these channels. As a result, the channel wastage due to the rate-independent MAC overheads can be reduced. We propose a protocol called WiSP (channel Width Selection based on Packet size) to estimate the appropriate channel widths depending on the relative traffic load involving short and long packets in the network. We evaluate our protocol using extensive simulations and demonstrate its effectiveness in achieving higher throughputs. We propose our algorithm to complement the frame aggregation (an existing approach that aggregates multiple packets to be sent in a single transmit opportunity) technique. We show that there are scenarios during which the frame aggregation can perform poorly, and show that our proposed algorithm can provide a good performance even in those situations when used along with frame aggregation.
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TL;DR: An efficient deterministic algorithm for consensus in presence of Byzantine failures achieves consensus on an L-bit value with communication complexity O(nL + n4L0.5 + n6) bits, in a network consisting of n processors with up to t Byzantine failures.
Abstract: In this paper, we present an efficient deterministic algorithm for consensus in presence of Byzantine failures. Our algorithm achieves consensus on an $L$-bit value with communication complexity $O(nL + n^4 L^{0.5} + n^6)$ bits, in a network consisting of $n$ processors with up to $t$ Byzantine failures, such that $t
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TL;DR: In this article, the authors investigated the capacity of the broadcast version of the Byzantine agreement problem in networks where communications links are capacity limited and showed that the output values of all fault-free nodes are equal.
Abstract: : In our previous work [5, 4, 6],we investigated the capacity of the broadcast version of the Byzantine agreement problem[3] in networks where communications links are capacity limited In this report, we are going to study capacity of the consensus version of the Byzantine agreement problem The Byzantine consensus problem considers n nodes, namely P1, , Pn, of which at most f nodes may be faulty and deviate from the algorithm in arbitrary fashion Each node Pi is given an input value vi, and they want to agree on a value v such that the following properties are satisfied: Termination: every fault-free Pi eventually decides on an output value v i , Consistency: the output values of all fault-free nodes are equal, ie, for every fault-free node Pi, v i = v for some v , Validity: if every fault-free Pi holds the same input vi = v for some v, then v = v
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TL;DR: NAB is the first algorithm that can achieve a constant fraction of capacity of Byzantine Broadcast (BB) in general point-to-point networks and proves an upper bound on the capacity.
Abstract: The goal of Byzantine Broadcast (BB) is to allow a set of fault-free nodes to agree on information that a source node wants to broadcast to them, in the presence of Byzantine faulty nodes. We consider design of efficient algorithms for BB in {\em synchronous} point-to-point networks, where the rate of transmission over each communication link is limited by its "link capacity". The throughput of a particular BB algorithm is defined as the average number of bits that can be reliably broadcast to all fault-free nodes per unit time using the algorithm without violating the link capacity constraints. The {\em capacity} of BB in a given network is then defined as the supremum of all achievable BB throughputs in the given network, over all possible BB algorithms.
We develop NAB -- a Network-Aware Byzantine broadcast algorithm -- for arbitrary point-to-point networks consisting of $n$ nodes, wherein the number of faulty nodes is at most $f$, $f
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09 Jun 2011