7471984
QoS supporting and optimal energy allocation for a cluster based wireless sensor network
Wireless sensor networks (WSNs) have become a very active and important area of research due to their potential in civil and military applications. A lot of research works focus on energy efficient routing protocols due to the limited energy of battery-powered nodes. Currently, the increasing interest in multimedia applications has made the QoS (quality of service) supporting an unavoidable task. In this paper, we perform the analysis of QoS supporting and optimal energy allocation issues by presenting a cluster based WSN. A QoS supporting scheme is developed for dynamic traffic conditions by controlling data generating rates at individual clusters. In addition, an explicit solution on the energy distribution at different clusters in the WSN is investigated based on an optimal energy allocation criterion. The localized QoS controlling scheme is useful in WSNs due to flexibility and scalability, and the obtained network energy distribution formula is particularly convenient for node deployment design in WSNs and three specific situations are discussed as applications.
36399349
Optimal (N, T)-policy for M/G/1 system with cost structures
Abstract In this paper, the optimal (N,T)-policy for M/G/1 system with cost structure is studied. The system operates only intermittently. It is shut down when no customers are present. A fixed set-up cost of K>0 is incurred each time the system is reopened. Also, a holding cost of h>0 per unit time is incurred for each customer present. The (N,T)-policy studied for this system is as follows: the system reactivates as soon as N customers are present or the waiting time of the leading customer reaches a predefined time T (see A.S. Alfa, I. Frigui, Eur. J. Oper. Res. 88 (1996) 599-613; Y.N. Doganata, in: E. Arikan (Ed.), Communication, Control, and Signal Processing, 1990, pp. 1663–1669). Later on, as a comparison, the start of the timer count is relaxed as follows: the system reactivates as soon as N customers are present or the time units after the end of the last busy period reaches a predefined time T. For both cases, the explicit optimal policy (N*,T*) for minimizing the long-run average cost per unit time are obtained. As extreme cases, we include the simple optimal policies for N-and T-polices. Several counter-intuitive results are obtained about the optimal T-policies for both types of models.
6504334
Modeling and analysis of hierarchical cellular networks with bidirectional overflow and take-back strategies under generally distributed cell residence times
The rapid growth of wireless services and mobile users drives a great interest in cellular networks with a hierarchical structure. Hierarchical cellular networks (HCNs) can provide high system capacity, efficient channel utilization and inherent load-balancing capability. In this paper, we develop an analytical model and a performance analysis method for a two-layer HCN with bidirectional overflow and take-back strategies. Mobile users are divided into two classes. The call requests (including new and handoff calls) of fast and slow users are preferably assigned to the macrolayer and microlayer, respectively. A call from a fast user or slow user can overflow to its non-preferable layer if there is no channel available. The successful overflow call can be taken back to its preferable layer if a channel becomes available. Since the commonly used exponentially distributed assumption for cell residence time and then the channel occupancy time does not hold for emerging mobile networks, we model various cell residence times by general distributions to adapt to more flexible mobility environments. The channel occupancy times are derived in terms of the Laplace transforms of various cell residence times. The handoff rates, overflow rates and take-back rates of each layer are also derived in terms of the new call arrival rates and related probabilities. The stationary probabilities (and then the performance measures) are determined on the basis of the theory of multi-dimensional loss systems.
17487983
A novel network allocation scheme in wireless mobile networks
A novel network allocation scheme of wireless mobile communications networks is investigated in this paper. We study the handoff rates of calls from one cell to another and obtain the blocking probabilities for new calls and handoff calls. Actual call connection time (ACCT) of a call is investigated, which is the total time a mobile user engaged in communications over a wireless network during a call connection and can be used to design appropriate charging schemes. Our numerical results show that how these measures depend on the new call arrival rate with specific reserved channels for handoff calls in each cell. These results are expected to be useful for the cost analysis for updating location and paging in wireless mobile network.
20117363
Performance analysis of a channel allocation scheme with preemptive priority for integrated voice/data mobile networks
This paper presents a new channel allocation scheme with preemptive priority for the integrated voice/data mobile network. Based on the scheme, a two-dimensional Markov process is built, and the steady-state probability is solved by the matrix-analytic method. The preemptive priority mechanism introduced gives more benefit to voice traffic at the expense of degrading some data traffic, while the victim buffer compensates the degradation and has no negative effect on voice traffic. From the analysis and numerical results, we can conclude that our scheme can guarantee different QoS requirements from different traffic classes, and significantly improve the channel utilization.
7393635
On a decomposition for infinite transition matrices
Heyman gives an interesting factorization of I-P, where P is the transition probability matrix for an ergodic Markov chain. We show that this factorization is valid if and only if the Markov chain is recurrent. Moreover, we provide a decomposition result which includes all ergodic, null recurrent as well as the transient Markov chains as special cases. Such a decomposition has been shown to be useful in the analysis of queues.
11433773
Email archive analysis through graphical visualization
The analysis of the vast storehouse of email content accumulated or produced by individual users has received relatively little attention other than for specific tasks such as spam and virus filtering. Current email analysis in standard client applications consists of keyword based matching techniques for filtering and expert driven manual exploration of email files. 
 We have implemented a tool, called the Email Mining Toolkit (EMT) for analyzing email archives which includes a graphical display to explore relationships between users and groups of email users. The chronological flow of an email message can be analyzed by EMT. Our design goal is to embed the technology into standard email clients, such as Outlook, revealing far more information about a user's own email history than is otherwise now possible. In this paper we detail the visualization techniques implemented in EMT. We show the utility of these tools and underlying models for detecting email misuse such as viral propagation, and spam spread as examples.
524613
Locating Compromised Sensor Nodes Through Incremental Hashing Authentication
While sensor networks have recently emerged as a promising computing model, they are vulnerable to various node compromising attacks. In this paper, we propose COOL, a COmpromised nOde Locating protocol for detecting and locating compromised nodes once they misbehave in the sensor network. We exploit a proven collision-resilient incremental hashing algorithm and design secure steps to confidently locate compromised nodes. The scheme can also be combined with existing en-route false report filtering schemes to achieve both early false report dropping and accurate compromised nodes isolation.
6649365
Performing Incremental Bayesian Inference by Dynamic Model Counting
The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 2005) demonstrates that the well-known Davis-Putnam procedure combined with a dynamic decomposition and caching technique is an effective method for exact inference in Bayesian networks with high density and width. In this paper, we define dynamic model counting and extend the dynamic decomposition and caching technique to multiple runs on a series of problems with similar structure. This allows us to perform Bayesian inference incrementally as the structure of the network changes. Experimental results show that our approach yields significant improvements over the previous model counting approaches on multiple challenging Bayesian network instances.
14087384
Rapid development of Hindi named entity recognition using conditional random fields and feature induction
This paper describes our application of conditional random fields with feature induction to a Hindi named entity recognition task. With only five days development time and little knowledge of this language, we automatically discover relevant features by providing a large array of lexical tests and using feature induction to automatically construct the features that most increase conditional likelihood. In an effort to reduce overfitting, we use a combination of a Gaussian prior and early stopping based on the results of 10-fold cross validation.
9473484
Bootstrapping for Named Entity Tagging Using Concept-based Seeds
A novel bootstrapping approach to Named Entity (NE) tagging using concept-based seeds and successive learners is presented. This approach only requires a few common noun or pronoun seeds that correspond to the concept for the targeted NE, e.g. he/she/man/woman for PERSON NE. The bootstrapping procedure is implemented as training two successive learners. First, decision list is used to learn the parsing-based NE rules. Then, a Hidden Markov Model is trained on a corpus automatically tagged by the first learner. The resulting NE system approaches supervised NE performance for some NE types.