Dynamic Leveling: Adaptive Data Broadcasting in a Mobile Computing Environment

The research issue of broadcasting has attracted a considerable amount of attention in a mobile computing system. By utilizing broadcast channels, a server is able to continuously and repeatedly broadcast data to mobile users. From these broadcast channels, mobile users obtain the data of interest efficiently and only need to wait for the required data to be present on the broadcast channel. Given the access frequencies of data items, one can design proper data allocation in the broadcast channels to reduce the average expected delay of data items. In practice, the data access frequencies may vary with time. We explore in this paper the problem of adjusting broadcast programs to effectively respond to the changes of data access frequencies, and develop an efficient algorithm DL to address this problem. Performance of algorithm DL is analyzed and a system simulator is developed to validate our results. Sensitivity analysis on several parameters, including the number of data items, the number of broadcast disks, and the variation of access frequencies, is conducted. It is shown by our results that the broadcast programs adjusted by algorithm DL are of very high quality and are in fact very close to the optimal ones.     

A study on channel allocation for data dissemination in mobile computing environments

This paper studies channel allocation methods for data dissemination through broadcast and ondemand channels. Analytical models and cost formulae for exclusive broadcast channels and exclusive ondemand channels are provided. Based on the models, we further derive cost models for dynamic channel allocation methods and propose a channel adaptation algorithm for optimizing system performance. The channel adaptation algorithm can be executed in O(n) time, where n is the number of data items in the database. Performance evaluation shows that the channel allocation algorithm produces optimal channel allocation which significantly improves the system performance under various parameter settings.     

Broadcast Disks with Polynomial Cost Functions

In broadcast disks systems, information is broadcasted in a shared medium. When a client needs an item from the disk, it waits until that item is broadcasted. Broadcast disks systems are particularly attractive in settings where the potential customers have a highly-asymmetric communication capabilities, i.e., receiving is significantly cheaper than transmitting. This is the case with satellite networks, mobile hosts in wireless networks, and Teletext system.The fundamental algorithmic problem for such systems is to determine the broadcast schedule based on the demand probability of items, and the cost incurred to the system by clients waiting. The goal is to minimize the mean access cost of a random client. Typically, it was assumed that the access cost is proportional to the waiting time. In this paper, we ask what are the best broadcast schedules for access costs which are arbitrary polynomials in the waiting time. These may serve as reasonable representations of reality in many cases, where the patience of a client is not necessarily proportional to its waiting time.We present an asymptotically optimal algorithm for a fractional model, where the bandwidth may be divided to allow for fractional concurrent broadcasting. This algorithm, besides being justified in its own right, also serves as a lower bound against which we test known discrete algorithms. We show that the Greedy algorithm has the best performance in most cases. Then we show that the performance of other algorithms deteriorate exponentially with the degree of the cost polynomial and approaches the fractional solution for sub-linear cost. Finally, we study the quality of approximating the greedy schedule by a finite schedule.     

On-Demand Data Broadcasting for Mobile Decision Making

The wide spread of mobile computing devices is transforming the newly emerged e-business world into a mobile e-business one, a world in which hand-held computers are the user's front-ends to access enterprise data. For good mobile decision making, users need to count on up-to-date, business-critical data. Such data are typically in the form of summarized information tailored to suit the user's analysis interests. In this paper, we are addressing the issue of time and energy efficient delivery of summary tables to mobile users with hand-held computers equipped with OLAP (On-Line Analytical Processing) front-end tools. Towards this, we propose a new on-demand scheduling algorithm, called STOBS, that exploits the derivation semantics among OLAP summary tables. It maximizes the aggregated data sharing between mobile users and reduces the broadcast length for satisfying a set of requests compared to the already existing techniques. The algorithm effectiveness with respect to access time and energy consumption is evaluated using simulation.     

Statistical Estimation of Access Frequencies: Problems, Solutions and Consistencies

In a wireless environment, a server periodically broadcasts data to users under an assumption that accurate access frequencies are known. The server broadcasts frequently accessed data more often in a broadcast cycle. The difficulty of obtaining such access frequencies is that, in a wireless environment, mobile users are only listening to the channel they are interested in and do not request the data items from the server. An approach in the literature is to make use of broadcast misses to understand the access patterns. In brief, mobile users may decide whether to wait for the required item to arrive (with uncertainty whether it will arrive soon or not) or to make an explicit request for it even though it will be broadcasted soon. In this paper, we extend our early work on access frequency estimations. First, we consider two cases: (a) a mobile user will make an explicit request when he/she cannot access the information immediately, and (b) a mobile user will make an explicit request with an arbitrary probability if he/she cannot access the information immediately. We assume that the probability is unknown. Second, we provide solutions using maximum likelihood estimation. Third, we prove -consistencies and m-consistencies of our solutions. We report our simulation study that demonstrates the effectiveness of our approach.     

On Channel Allocation for Heterogeneous Data Broadcasting

We explore in this paper the problem of generating broadcast programs in a heterogeneous data broadcasting environment, in which disseminated data items can be of different sizes. Given the broadcast database and the number of channels, we first derive the analytical model of the heterogeneous data broadcasting to obtain the average waiting time of mobile users, and prove the allocation problem as an NP-complete problem. In order to solve such problem, we propose a two-phase architecture to perform channel allocation. Algorithm DRP (Dimension Reduction Partitioning) is employed to perform rough allocation to derive the satisfactory solutions, whereas mechanism CDMS (Cost-Diminishing Movement Selection) is used for fine allocation to achieve local optimum solutions. In addition, we also propose algorithm GA-CDMS according to the concept of hybrid genetic algorithm for comparison purposes. GA-CDMS can perform global search more accurately and efficiently than conventional genetic algorithm GA and the suboptimum that GA-CDMS achieves will be very close to the optimal solution. In the experiments, we consider the important issues such as accuracy, scalability, diversity and the efficiency. From the experimental results, we show that the proposed two-phase channel allocation is very practical in performing an effective channel allocation with high efficiency in a heterogeneous broadcasting environment.     

Indexing Techniques for Power Management in Multi-Attribute Data Broadcast

In this paper, we discuss the power conservative indexing techniques for managing multi-attribute data broadcast on wireless channels. These indexing techniques, namely, index tree, signature and hybrid, aim at improving the battery power consumption of mobile clients. By taking into account the broadcast management factors such as clustering and scheduling, these three indexing schemes may significantly reduce tune-in time while maintaining a reasonable access time. Cost models for single and multi-attribute query processing are developed. Our performance evaluation shows that the signature and hybrid methods are superior to the index tree method.     

Opportunistic interference management: a new approach for multiantenna downlink cellular networks

A new approach for multiantenna broadcast channels in cellular networks based on multiuser diversity concept is introduced. The technique called opportunistic interference management achieves dirty paper coding capacity asymptotically with minimum feedback required. When there are K antennas at the base station with M mobile users in the cell, the proposed technique only requires K integer numbers related to channel state information between mobile users and base station. The encoding and decoding complexity of this scheme is the same as that of point‐to‐point communications, which makes the implementation of this technique easy. An antenna selection scheme is proposed at the base station to reduce the minimum required mobile users significantly at the expense of reasonable increase in feedback. In order to guarantee fairness, a new algorithm is presented that incorporates opportunistic interference management into existing Global System for Mobile communications (GSM) standard. Copyright © 2014 John Wiley & Sons, Ltd.     

A Five-Phase Reservation Protocol (FPRP) for Mobile Ad Hoc Networks

A new single channel, time division multiple access (TDMA)-based broadcast scheduling protocol, termed the Five-Phase Reservation Protocol (FPRP), is presented for mobile ad hoc networks. The protocol jointly and simultaneously performs the tasks of channel access and node broadcast scheduling. The protocol allows nodes to make reservations within TDMA broadcast schedules. It employs a contention-based mechanism with which nodes compete with each other to acquire TDMA slots. The FPRP is free of the hidden terminal problem, and is designed such that reservations can be made quickly and efficiently with negligible probability of conflict. It is fully-distributed and parallel (a reservation is made through a localized conversation between nodes in a 2-hop neighborhood), and is thus scalable. A multihop ALOHA policy is developed to support the FPRP. This policy uses a multihop, pseudo-Bayesian algorithm to calculate contention probabilities and enable faster convergence of the reservation procedure. The performance of the protocol, measured in terms of scheduling quality, scheduling overhead and robustness in the presence of nodal mobility, has been studied via simulations. The results showed that the protocol works very well in all three aspects. Some future work and applications are also discussed.     

Exploiting replication on dependent data allocation for ordered queries over multiple broadcast channels

Data broadcasting has been recognized as an important means for information dissemination in mobile computing environments. In some mobile applications, the data items broadcast are dependent upon one another. However, most prior studies on broadcasting dependent data do not employ replication in broadcast program generation. In view of this, we explore in this paper the problem of broadcasting dependent data in multiple broadcast channels, and explicitly investigate the effect of data replication. After analyzing the model of dependent data broadcasting, we derive several theoretical properties to formulate the average access time of broadcast programs. In light of the theoretical results, we develop an algorithm to exploit replication on broadcast program generation. Our experimental results show that the proposed algorithm is able to generate broadcast programs of very high quality. In addition, the results also show that broadcast programs with replication is more robust than those without replication in error-prone environments.     

Minimum-Energy Broadcasting in Multi-hop Wireless Networks Using a Single Broadcast Tree

In this paper we address the minimum-energy broadcast problem in multi-hop wireless networks, so that all broadcast requests initiated by different source nodes take place on the same broadcast tree. Our approach differs from the most commonly used one where the determination of the broadcast tree depends on the source node, thus resulting in different tree construction processes for different source nodes. Using a single broadcast tree simplifies considerably the tree maintenance problem and allows scaling to larger networks. We first show that, using the same broadcast tree, the total power consumed for broadcasting from a given source node is at most twice the total power consumed for broadcasting from any other source node. We next develop a polynomial-time approximation algorithm for the construction of a single broadcast tree. The performance analysis of the algorithm indicates that the total power consumed for broadcasting from any source node is within 2H(n−1) from the optimal, where n is the number of nodes in the network and H(n) is the harmonic function. This approximation ratio is close to the best achievable bound in polynomial time. We also provide a useful relation between the minimum-energy broadcast problem and the minimum spanning tree, which shows that a minimum spanning tree may be a good candidate in sparsely connected networks. The performance of our algorithm is also evaluated numerically with simulations. A preliminary version of this work appeared in the Proceedings of WiOpt’04: Modeling and Optimization in Mobile, Ad hoc and Wireless Networks, University of Cambridge, UK, March 2004. Ioannis Papdimitriou was fully supported for this work by the Public Benefit Foundation “ALEXANDER S. ONASSIS”, Athens, Greece. Ioannis Papadimitriou was born in Veria, Greece, in 1976. He received his five year Diploma from the Department of Electronic and Computer Engineering, Technical University of Crete (Chania), Greece, in 1999 (graduating 2nd in class). He is currently a postgraduate student - Ph.D. candidate at the Telecommunications division, Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Greece. His doctoral thesis deals with the design of wireless ad hoc networks. His research interests include broadcast and multicast communication, energy conservation, routing and topology control protocols, MAC layer and QoS issues. During his studies he has been honored with awards and scholarships by the Technical University of Crete, the Hellenic Telecommunications Organization S.A.(OTE S.A.) and Ericsson Hellas S.A. Mr. Papadimitriou has been a member of the Technical Chamber of Greece (TEE) since March 2000, and he has been supported by the Public Benefit Foundation ALEXANDER S. ONASSIS, Athens, Greece, with a scholarship for his doctoral studies from October 2001 to March 2005. Leonidas Georgiadis received the Diploma degree in electrical engineering from Aristotle University, Thessaloniki, Greece, in 1979, and his M.S. and Ph.D. degrees both in electrical engineering from the University of Connecticut, in 1981 and 1986, respectively. From 1981 to 1983 he was with the Greek army. From 1986 to 1987 he was Research Assistant Professor at the University of Virginia, Charlottesville. In 1987 he joined IBM T.J. Watson Research Center, Yorktown Heights, as a Research Staff Member. Since October 1995, he has been with the Telecommunications Department of Aristotle University, Thessaloniki, Greece. His interests are in the area of wireless networks, high speed networks, distributed systems, routing,scheduling, congestion control, modeling and performance analysis. Prof. Georgiadis is a senior member of IEEE Communications Society. In 1992 he received the IBM Outstanding Innovation Award for his work on goal-oriented workload management for multi-class systems.x     

A Broadcast Mechanism Supporting Power-Conserving Mobile Stations<Superscript>*</Superscript>

Power saving is an important issue in the mobile computing environment. In this paper, we propose a broadcast mechanism which constructs the broadcast channels according to the access frequency of each disseminated kind of message in order to save power in mobile stations. The pinwheel scheduling algorithm presented in this paper is used to organize all kinds of messages in the broadcast channels in a most symmetrical distribution for reducing both tuning time and access time. Performance of the proposed mechanism is analyzed and the improvement is demonstrated with numerical results. The results show that the proposed mechanism is capable improving both tuning time and access time as the skew access characteristic exists among the disseminated messages. ^*This work was supported in part by the National Science of Council, R.O.C., under Contract NSC94-2213-E-130-003.     

A Distributed Algorithm for Dynamic Channel Allocation

Recent demand for mobile telephone service has been growing rapidly while the electro-magnetic spectrum of frequencies allocated for this purpose remains limited. Any solution to the channel assignment problem is subject to this limitation, as well as the interference constraint between adjacent channels in the spectrum. Channel allocation schemes provide a flexible and efficient access to bandwidth in wireless and mobile communication systems. In this paper, we present an efficient distributed algorithm for dynamic channel allocation based upon mutual exclusion model, where the channels are grouped by the number of cells in a cluster and each group of channels cannot be shared concurrently within the cluster. We discuss the algorithm and prove its correctness. We also show that the algorithm requires at most (worst case) O(N _gN _n logN _n) messages, where N _g is the number of groups and N _n is the number of neighbors. This is compared to Choy's algorithm which requires O(N _g ²N _n), where N _g is the number of groups and N _n is the number of neighboring cells in the system. We report our algorithm's performance with several channel systems using different types of call arrival patterns. Our results indicate that significant low denial rate, low message complexity and low acquisition time can be obtained using our algorithm.     

Selecting Forwarding Neighbors in Wireless Ad Hoc Networks

Broadcasting is a fundamental operation which is frequent in wireless ad hoc networks. A simple broadcasting mechanism, known as flooding, is to let every node retransmit the message to all its 1-hop neighbors when receiving the first copy of the message. Despite its simplicity, flooding is very inefficient and can result in high redundancy, contention, and collision. One approach to reducing the redundancy is to let each node forward the message only to a small subset of 1-hop neighbors that cover all of the node's 2-hop neighbors. In this paper we propose two practical heuristics for selecting the minimum number of forwarding neighbors: an O(nlogn) time algorithm that selects at most 6 times more forwarding neighbors than the optimum, and an O(nlog² n) time algorithm with an improved approximation ratio of 3, where n is the number of 1- and 2-hop neighbors. The best previously known algorithm, due to Bronnimann and Goodrich [2], guarantees O(1) approximation in O(n ³ logn) time.     

Energy efficient broadcast routing in mobile ad hoc networks

In this paper, we address the problem of broadcast routing in mobile ad hoc networks from the viewpoint of energy efficiency. In an ad hoc wireless network, each node runs on a local energy source which has a limited energy lifespan. Thus, energy conservation is a critical issue in ad hoc networks. One approach for energy conservation is to establish routes which require lowest total energy consumption. This optimization problem is referred as the minimum‐energy broadcast routing problem (MEBRP). In this paper, we propose new efficient algorithms for the construction of energy‐efficient trees for broadcast in mobile ad hoc networks. These algorithms exploit the broadcast nature of the wireless channel, and address the need for energy‐efficient operations. Empirical studies show that our algorithms are able to achieve better performance than algorithms that have been developed for MEBRP. Copyright © 2004 John Wiley & Sons, Ltd.     

SOM: dynamic push-pull channel allocation framework for mobile data broadcasting

In a mobile computing environment, the combined use of broadcast and on-demand channels can utilize the bandwidth effectively for data dissemination. We explore in this paper the problem of dynamic data and channel allocation with the number of communication channels and the number of data items given. We first derive the analytical models of the average access time when the data items are requested through the broadcast and on-demand channels. Then, we transform this problem into a guided search problem. In light of the theoretical properties derived, we devise algorithm SOM to obtain the optimal allocation of data and channels. Algorithm SOM is a composite algorithm which will cooperate with 1) a search strategy and 2) a broadcast program generation algorithm. According to the analytical mode, we devise scheme BIS-incremental on the basis of algorithm SOM, which is able to obtain solutions of high quality efficiently by employing binary interpolation search. In essence, scheme BIS-incremental is guided to explore the search space with higher likelihood to be the optimal first, thereby leading to an efficient and effective search. It is shown by our simulation results that the solution obtained by scheme BIS-incremental is of very high quality and is in fact very close to the optimal one. A sensitivity study on several parameters, including the number of data items and the number of communication channels, is conducted. The experimental results show that scheme BIS-incremental is of very good scalability, which is particularly important for its practical use in a mobile computing environment.     

Approximation Algorithms for the Mobile Piercing Set Problem with Applications to Clustering in Ad-Hoc Networks

The main contributions of this paper are two-fold. First, we present a simple, general framework for obtaining efficient constant-factor approximation algorithms for the mobile piercing set (MPS) problem on unit-disks for standard metrics in fixed dimension vector spaces. More specifically, we provide low constant approximations for L ₁ and L norms on a d-dimensional space, for any fixed d>0, and for the L ₂ norm on two- and three-dimensional spaces. Our framework provides a family of fully-distributed and decentralized algorithms, which adapt (asymptotically) optimally to the mobility of disks, at the expense of a low degradation on the best known approximation factors of the respective centralized algorithms: Our algorithms take O(1) time to update the piercing set maintained, per movement of a disk. We also present a family of fully-distributed algorithms for the MPS problem which either match or improve the best known approximation bounds of centralized algorithms for the respective norms and space dimensions.Second, we show how the proposed algorithms can be directly applied to provide theoretical performance analyses for two popular 1-hop clustering algorithms in ad-hoc networks: the lowest-id algorithm and the Least Cluster Change (LCC) algorithm. More specifically, we formally prove that the LCC algorithm adapts in constant time to the mobility of the network nodes, and minimizes (up to low constant factors) the number of 1-hop clusters maintained. While there is a vast literature on simulation results for the LCC and the lowest-id algorithms, these had not been formally analyzed prior to this work.We also present an O(logn)-approximation algorithm for the mobile piercing set problem for nonuniform disks (i.e., disks that may have different radii), with constant update time.     

A Cost-Efficient Scheduling Algorithm of On-Demand Broadcasts

In mobile wireless systems data on air can be accessed by a large number of mobile users. Many of these applications including wireless internets and traffic information systems are pull-based, that is, they respond to on-demand user requests. In this paper, we study the scheduling problems of on-demand broadcast environments. Traditionally, the response time of the requests has been used as a performance measure. In this paper we consider the performance as the average cost of request composed of three kinds of costs – access time cost, tuning time cost, and cost of handling failure request. Our main contribution is a self-adaptive scheduling algorithm named LDFC, which computes the delay cost of data item as the priority of broadcast. It costs less compared with some previous algorithms in this context, and shows good adaptability as well even in pure push-based broadcasts.     

Response Time Analysis in a Data Broadcast System with User Cache

Data broadcast has been considered a promising way of information dissemination to a massive number of users in a wireless communication environment. Reducing user-waiting time is a major problem in developing a data broadcast system. There are two approaches for this problem; One is to design a broadcast schedule at the server side which reduces the mean response time, and the other is to utilize a local cache at the user side which may respond to a user request instantly. Though these two approaches were addressed separately in the literature, they may be taken jointly for better performance. The performance of system with joint approach depends on several factors such as broadcast schedule, cache size, cache management strategy, etc. In this paper we analyze response time in a data broadcast system with joint approach in which information items are structurally related with each other as in WWW. Based on the worst-case assumption, we derive a lower bound on the system performance for a given set of broadcast schedule, cache size, and cache management strategy. This result will be of help for designing and developing a data broadcast system. We support our analysis by carrying out an extensive simulation on some interesting proposed broadcast schedules and cache management strategies.     

Response Time in Data Broadcast Systems: Mean,Variance and Tradeoff

Data broadcast has been suggested as a promising method of information dissemination [2,33]. In such an environment, the information server cannot afford to serve the requests from a large population of users individually. Instead, the server uses a broadcast channel to deliver information to all users. A single transmission of a data item satisfies all pending requests for that item. The response time of a request depends on the broadcast time of the desired data item, which is scheduled by the server according to the overall demands for various data items. Therefore, the response time may vary in a large range. We argue that, in addition to mean response time, the variance of response time should also be taken into account by the broadcast scheduler. In this paper, we address the issue of variance optimization in regard to response time. Building on our previous research on mean response time optimization, we propose an algorithm which can minimize the variance of response time. Furthermore, we evaluate an algorithm that facilitates a tradeoff between the mean and variance of response time. Numerical examples that illustrate the performance of our algorithms are also presented.