20717190
Opportunistic power scheduling for multi-server wireless systems with minimum performance constraints
We present and power scheduling scheme, i.e., a joint time-slot and power allocation method for wireless cellular systems. We allow multiple transmissions in a time-slot that can interfere with each other. Hence, it is important to not only select the mobiles to he scheduled in a time-slot, hut also important to allocate an appropriate power level for transmission to these scheduled mobiles in order to achieve high system performance and quality of service. We model the time-varying wireless channel as a stochastic process and formulate a stochastic programming problem that attempts to maximize the expected total system utility, with constraints on the minimum expected utility for each mobile. The power scheduling algorithm is obtained by using stochastic duality and implemented via stochastic subgradient techniques.
7032611
Utility-Optimal Medium Access Control: Reverse and Forward Engineering
This paper analyzes and designs medium access control (MAC) protocols for wireless ad-hoc networks through the network utility maximization (NUM) framework. We first reverse-engineer the current exponential backoff (EB) type of MAC protocols such as the BEB (binary exponential backoff) in the IEEE 802.11 standard through a non-cooperative game- theoretic model. This MAC protocol is shown to be implicitly maximizing, using a stochastic subgradient, a selfish local utility at each link in the form of expected net reward for successful transmission. While the existence of a Nash equilibrium can be established, neither convergence nor social welfare optimality is guaranteed due to the inadequate feedback mechanism in the EB protocol. This motivates the forward-engineering part of the paper, where a network-wide utility maximization problem is for- mulated, using a collision and persistence probability model and aligning selfish utility with total social welfare. By adjusting the parameters in the utility objective functions of the NUM problem, we can also control the tradeoff between efficiency and fairness of radio resource allocation through a rigorous and systematic design. We develop two distributed algorithms to solve the MAC design NUM problem, which lead to random access protocols that have slightly more message passing overhead than the current EB protocol, but significant potential for efficiency and fairness improvement. We provide readily-verifiable sufficient conditions under which convergence of the proposed algorithms to a global optimality of network utility can be guaranteed, and through numerical examples illustrate the value of the NUM approach to the complexity-performance tradeoff in MAC design.
7887291
Non-convex optimization and rate control for multi-class services in the Internet
In this paper, we investigate the problem of distributively allocating transmission data rates to users in the Internet. We allow users to have concave as well as sigmoidal utility functions as appropriate for different applications. In the literature, for simplicity, most works have dealt only with the concave utility function. However, we show that applying rate control algorithms developed for concave utility functions in a more realistic setting (with both concave and sigmoidal types of utility functions) could lead to instability and high network congestion. We show that a pricing-based mechanism that solves the dual formulation can be developed based on the theory of subdifferentials with the property that the prices "self-regulate" the users to access the resources based on the net utility. We discuss convergence issues and show that an algorithm can be developed that is efficient in the sense of achieving the global optimum when there are many users.
16820775
Nonconvexity issues for Internet rate control with multiclass services: stability and optimality
In this paper, we investigate the problem of distributively allocating transmission rates to users on the Internet. We allow users to have concave as well as sigmoidal utility functions that are natural in the context of various applications. In the literature, for simplicity, most works have dealt only with the concave case. However, we show that when applying rate control algorithms developed for concave utility functions in a more realistic setting (with both concave and sigmoidal types of utility functions), they could lead to instability and high network congestion. We show that a pricing based mechanism that solves the dual formulation can be developed based on the theory of subdifferentials with the property that the prices "self-regulate" the users to access the resource based on the net utility. We discuss convergence issues and show that an algorithm can be developed that is efficient in the sense of achieving the global optimum when there are many users.
16485757
Reverse Engineering MAC
This paper reverse engineers backoff-based random-access MAC protocols in ad-hoc networks. We show that the contention resolution algorithm in such protocols is implicitly participating in a non-cooperative game. Each link attempts to maximize a selfish local utility function, whose exact shape is reverse engineered from the protocol description, through a stochastic subgradient method in which the link updates its persistence probability based on its transmission success or failure. We prove that existence of a Nash equilibrium is guaranteed in general. The minimum amount of backoff aggressiveness needed for uniqueness of Nash equilibrium and convergence of the best response strategy are established as a function of user density. Convergence properties and connection with the best response strategy are also proved for variants of the stochastic-subgradient-based dynamics of the game. Together with known results in reverse engineering TCP and BGP, this paper completes the recent efforts in reverse engineering the main protocols in layers 2-4.
47092701
Loop formulas for circumscription
Clark's completion is a simple nonmonotonic formalism and a special case of many nonmonotonic logics. Recently there has been work on extending completion with "loop formulas" so that general cases of nonmonotonic logics such as logic programs (under the answer set semantics) and McCain-Turner causal logic can be characterized by propositional logic in the form of "comple(ion + loop formulas". In this paper, we show that the idea is applicable to McCarthy's circumscription in the propositional case. We also show how to embed propositional circumscription in logic programs and in causal logic, inspired by the uniform characterization of "completion + loop formulas".
11330211
Resolving References to Graphical Objects in Multimodal Queries by Constraint Satisfaction
In natural language queries to an intelligent multimodal system, ambiguities related to referring expressions - source ambiguities - can occur between items in the visual display and objects in the domain being represented. A multimodal interface has to be able to resolve these ambiguities in order to provide satisfactory communication with a user. In this paper, we briefly introduce source ambiguities, and present the formalisation of a constraint satisfaction approach to interpreting singular referring expressions with source ambiguities. In our approach, source ambiguities are resolved simultaneously with other referent ambiguities, allowing flexible access to various sorts of knowledge.
13362734
FINDIT: a fast and intelligent subspace clustering algorithm using dimension voting
Abstract The aim of this paper is to present a novel subspace clustering method named FINDIT. Clustering is the process of finding interesting patterns residing in the dataset by grouping similar data objects from dissimilar ones based on their dimensional values. Subspace clustering is a new area of clustering which achieves the clustering goal in high dimension by allowing clusters to be formed with their own correlated dimensions. In subspace clustering, selecting correct dimensions is very important because the distance between points is easily changed according to the selected dimensions. However, to select dimensions correctly is difficult, because data grouping and dimension selecting should be performed simultaneously. FINDIT determines the correlated dimensions for each cluster based on two key ideas: dimension-oriented distance measure which fully utilizes dimensional difference information, and dimension voting policy which determines important dimensions in a probabilistic way based on V nearest neighbors' information. Through various experiments on synthetic data, FINDIT is shown to be very successful in the high dimensional clustering problem. FINDIT satisfies most requirements for good clustering methods such as accuracy of results, robustness to the noise and the cluster density, and scalability to the dataset size and the dimensionality. Moreover, it is gracefully scalable to full dimension without any modification to algorithm.
2796328
Adaptive beamforming with multiple-beam constraints in the presence of coherent jammers
Abstract This paper deals with the problem of adaptive beamforming using a uniform linear array to provide multiple-beam constraints and suppress coherent jammers simultaneously. By constructing a steering matrix with each column vector corresponding to the steering vector of a selective beam and a constraint vector with each entry equal to the gain of a selective beam, we can achieve an adaptive array beamformer with multiple-beam constraints. For coping with the performance degradation due to the presence of coherent jammers, a matrix reconstruction scheme in conjunction with an iterative algorithm is presented to alleviate the coherent jamming effect. Simulation examples for illustration and comparison are also given.
9924413
On a unified architecture for video-on-demand services
Current video-on-demand (VoD)) systems can be classified into two categories: 1) true-Voll) (TVoD) and 2) near-VoD (NVod)). TVoD systems allocate a dedicated channel for every user to achieve short response times so that the user can select what video to play, when to play it, and perform interactive VCR-like controls at will. By contrast, NVoD systems transmit videos repeatedly over multiple broadcast or multicast channels to enable multiple users to share a single video channel so that system cost can be substantially reduced. The tradeoffs are limited video selections, fixed playback schedule, and limited or no interactive control. TVoD systems can be considered as one extreme where service quality is maximized, while NVoD systems can be considered as the other extreme where system cost is minimized. This paper proposes a novel architecture called Unified VoD) (UVoD) that can be configured to achieve cost-performance tradeoff anywhere between the two extremes (i.e., TVoD and NVoD). Assuming that a video client can concurrently receive two video channels and has local buffers for caching a portion of the video data, the proposed UVoD architecture can achieve significant performance gains (e.g., 400% more capacity for a 500-channel system) over TVoD under the same latency constraint. This paper presents the UVoD architecture, establishes a performance model, and analyzes UVoD's performance via numerical and simulation results.