High Performance Data Broadcasting Systems

Data broadcasting as a means of efficient data dissemination is a key technology facilitating ubiquitous computing. For this reason, broadcast scheduling algorithms have received a lot of attention. However, all existing algorithms make the core assumption that the data items to be broadcast are immediately available in the transmitter's queue, ignoring the key role that the disk subsystem and the cache management play in the overall broadcast system performance. With this paper we contribute a comprehensive system's perspective towards the development of high performance broadcast systems, taking into account how broadcast scheduling, disk scheduling, and cache management algorithms affect the overall performance. We contribute novel techniques that ensure an efficient interplay between broadcast scheduling, cache management, and disk scheduling. We study comprehensively the performance of the broadcast server, as it consists of the broadcast scheduling, the disk scheduling, the cache management algorithms, and the transmitter. Our results show that the contributed algorithms yield considerably higher performance. Furthermore, one of our algorithms is shown to enjoy considerably higher performance, under all values of the problem and system parameters. A key contribution is the result that broadcast scheduling algorithms have only a small effect on the overall system performance, which necessitates the definition of different focal points for efforts towards high performance data broadcasting.     

Simulation Models for Investigation of Multiuser Scheduling in MIMO Broadcast Channels

Spatial correlation is a result of insufficient antenna spacing among multiple antenna elements, while temporal correlation is caused by Doppler spread. This paper compares the effect of spatial and temporal correlation in order to investigate the performance of multiuser scheduling algorithms in multiple‐input multiple‐output (MIMO) broadcast channels. This comparison includes the effect on the ergodic capacity, on fairness among users, and on the sum‐rate capacity of a multiuser scheduling algorithm utilizing statistical channel state information in spatio‐temporally correlated MIMO broadcast channels. Numerical results demonstrate that temporal correlation is more meaningful than spatial correlation in view of the multiuser scheduling algorithm in MIMO broadcast channels. Indeed, the multiuser scheduling algorithm can reduce the effect of the Doppler spread if it exploits the information of temporal correlation appropriately. However, the effect of spatial correlation can be minimized if the antenna spacing is sufficient in rich scattering MIMO channels regardless of the multiuser scheduling algorithm used.     

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 the optimality of multiantenna broadcast scheduling using zero-forcing beamforming

Although the capacity of multiple-input/multiple-output (MIMO) broadcast channels (BCs) can be achieved by dirty paper coding (DPC), it is difficult to implement in practical systems. This paper investigates if, for a large number of users, simpler schemes can achieve the same performance. Specifically, we show that a zero-forcing beamforming (ZFBF) strategy, while generally suboptimal, can achieve the same asymptotic sum capacity as that of DPC, as the number of users goes to infinity. In proving this asymptotic result, we provide an algorithm for determining which users should be active under ZFBF. These users are semiorthogonal to one another and can be grouped for simultaneous transmission to enhance the throughput of scheduling algorithms. Based on the user grouping, we propose and compare two fair scheduling schemes in round-robin ZFBF and proportional-fair ZFBF. We provide numerical results to confirm the optimality of ZFBF and to compare the performance of ZFBF and proposed fair scheduling schemes with that of various MIMO BC strategies.     

Minimizing broadcast latency and redundancy in asynchronous wireless sensor networks

Asynchronous duty cycle Medium Access Control (MAC) protocols do not require global synchronization because nodes determine their wake-up schedule independently. As a result, these MACs have superior performance to those that employ synchronous duty-cycles in terms of energy expenditure, and advantageously, they are simple to implement. A key limitation is that they do not support efficient broadcast. A node needs to transmit a broadcast packet multiple times via unicast because only a subset of its neighbors may be awake at any given point in time. To address this problem, this paper proposes a centralized and distributed asynchronous broadcast algorithm that achieves minimal broadcast latency and redundancy. In addition, it uses a novel asynchronous MAC protocol that ensures all neighbors of a broadcasting node are awake to receive a broadcast. The performance of our algorithms is evaluated under different network configurations. We show via extensive simulation studies that our algorithms have near optimal network performance in terms of broadcast latency. In particular, compared to OTAB, the best broadcast scheduling algorithm to date, the broadcast latency and transmission times achieved by our designs are 1/5 and 1/2 that of OTAB, respectively.     

Efficient algorithms for scheduling data broadcast

With the increasing acceptance of wireless technology, mechanisms to efficiently transmit information to wireless clients are of interest. The environment under consideration is asymmetric in that the information server has much more bandwidth available, as compared to the clients. It has been proposed that in such systems the server should broadcast the information periodically. A broadcast schedule determines what is broadcast by the server and when. This paper makes the simple, yet useful, observation that the problem of broadcast scheduling is related to the problem of fair queueing. Based on this observation, we present a log‐time algorithm for scheduling broadcast, derived from an existing fair queueing algorithm. This algorithm significantly improves the time‐complexity over previously proposed broadcast scheduling algorithms. Modification of this algorithm for transmissions that are subject to errors is considered. Also, for environments where different users may be listening to different number of broadcast channels, we present an algorithm to coordinate broadcasts over different channels. Simulation results are presented for proposed algorithms.     

Optimal broadcast scheduling in packet radio networks using meanfield annealing

We present an efficient broadcast scheduling algorithm based on mean field annealing (MFA) neural networks. Packet radio (PR) is a technology that applies the packet switching technique to the broadcast radio environment. In a PR network, a single high-speed wideband channel is shared by all PR stations. When a time-division multi-access protocol is used, the access to the channel by the stations' transmissions must be properly scheduled in both the time and space domains in order to avoid collisions or interferences. It is proven that such a scheduling problem is NP-complete. Therefore, an efficient polynomial algorithm rarely exists, and a mean field annealing-based algorithm is proposed to schedule the stations' transmissions in a frame consisting of certain number of time slots. Numerical examples and comparisons with some existing scheduling algorithms have shown that the proposed scheme can find near-optimal solutions with reasonable computational complexity. Both time delay and channel utilization are calculated based on the found schedules     

无线自组网中基于离散粒子群优化的睡眠调度感知最小功率广播

针对当网络使用睡眠调度并且节点的传输功率连续可调节时的最小功率广播调度问题,首先给出了一种计算节点内部最优发送调度的递归方法,然后提出了一种构造最小功率广播调度的离散粒子群算法。该算法搜索最优广播树结构,并融合基于最小广播功率增量的贪心算法和基于启发式调整广播树结构的局部优化算法以提高收敛速度和求解质量。模拟实验结果表明所提算法能够有效地减少广播功率。     

Client-Side Caching Strategies and On-Demand Broadcast Algorithms for Real-Time Information Dispatch Systems

In this work, we propose a broadcast algorithm called Most Request Served (MRS) and its variants with caching strategies for on-time delivery of data in Real-Time Information Dispatch System. This family of algorithms consider request deadline, data object size and data popularity in making scheduling decisions. Although previous scheduling algorithms also base on some or all of these attributes to choose the most beneficial data to be broadcast, they did not consider the loss brought by their scheduling decisions. However, MRS considers both gain and loss in making a scheduling decision. We have performed a series of simulation experiments to compare the performance of various algorithms. Simulation results show that our proposed broadcast algorithm not only succeeds in providing good on-time delivery of data but at the same time provides 20% of improvement in response time over traditional scheduling algorithms like First-In-First-Out (FIFO) and Earliest-Deadline-First (EDF). Simulation results also show that our proposed caching strategy provides further improvement in terms of percentage of requests finished in time over traditional caching strategy like Least Recently Used (LRU).     

Real-Time Data Delivery Using Prediction Mechanism in Mobile Environments

Mobile data delivery is a critical issue in the mobile computing area. One of the most important problems is the efficient access to data. A proposed solution to this problem is the prefetching technique which consists in putting in reserving the information before the users need it. Low bandwidth, unreliable wireless links, and frequent disconnections of mobile environments make it difficult to satisfy the timing requirements of traditional strategies. This paper investigates broadcast scheduling strategies for push-based broadcast with timing constraints in the form of deadlines ,and proposes a prediction algorithm based on Kalman filter theory for this study. The proposed dissemination policy and adaptive bandwidth allocation scheme obtain sufficient conditions such that all the time-bounded traffic sources satisfy their timing constraints to provide various quality of service guarantees in the broadcast period. Our goal is to identify scheduling algorithms for broadcast systems that ensure requests meeting their deadlines. Our approach examines the performance of traditional real-time strategies and mobile broadcasting strategies, and demonstrates that traditional real-time algorithms do not always perform the best in mobile environments. The proposed design indeed achieves good performance in mobile environments.     

Performance analysis of SIMO space-time scheduling with convex utility function: zero-forcing linear processing

In a multiple-antenna system, an optimized design across the link and scheduling layers is crucial toward fully exploiting the temporal and spatial dimensions of the communication channel. In this paper, based on discrete optimization techniques, we derive a novel analytical framework for designing optimal space-time scheduling algorithms with respect to general convex utility functions. We focus on the reverse link (i.e., client to base station) and assume that the mobile terminal has a single transmit antenna while the base station has n/sub R/ receive antennas. In order that our proposed framework is practicable and can be implemented with a reasonable cost in a real environment, we further assume that the physical layer involves only linear-processing complexity in separating signals from different users. As an illustration of the efficacy of our proposed analytical design framework, we apply the framework to two commonly used system utility functions, namely maximal throughput and proportional fair. We then devise an optimal scheduling algorithm based on our design framework. However, in view of the formidable time complexity of the optimal algorithm, we propose two fast practical scheduling techniques, namely the greedy algorithm and the genetic algorithm (GA). The greedy algorithm, which is similar to the one widely used in 3G1X and Qualcomm high-data-rate (HDR) systems (optimal when n/sub R/=1), exhibits significantly inferior performance when n/sub R/>1 as compared with the optimal approach. On the other hand, the GA is quite promising in terms of performance complexity tradeoff, especially for a system with a large number of users with even a moderately large n/sub R/. As a case in point, for a system with 20 users and n/sub R/=4, the GA is more than 36 times faster than the optimal while the performance degradation is less than 10%, making it an attractive choice in the practical implementation for real-time link scheduling.     

Broadcast Scheduling in Interference Environment

Broadcast is a fundamental operation in wireless networks and naive flooding is not practical because it cannot deal with interference. Scheduling is a good way to avoid interference, but previous studies on broadcast scheduling algorithms all assume highly theoretical models such as the unit disk graph model. In this work, we re-investigate this problem using the 2-Disk and the signal-to-interference-plus-noise-ratio (SINR) model to realize it. We first design a constant approximation algorithm for the 2-Disk model and then extend it to the SINR model. This result is the first result on broadcast scheduling algorithms in SINR model, to the best of our knowledge.     

NEST: novel eMBMS scheduling technique

In order to meet the growing demand for mobile multimedia broadcast services 3GPP includes evolved multimedia broadcast and multicast (eMBMS) services in LTE systems. The high data rates, low latency and QoS provisioning makes LTE systems more suitable for mobile broadcast and multicast services than legacy wireless networks. However, the 3GPP standards has not specified any scheduling strategy for this broadcast and multicast services. In this paper, we propose a novel eMBMS scheduling technique (NEST) which focuses on reducing the average waiting time (latency) of the broadcast services offered by LTE system. This paper has twofold contributions. We proffer NEST considering two types of impatience that is user equipment (UE) departure and UE request repetition. Our proposed scheduling strategy estimates the effects originating from the departure of the mobile UEs and UE request repetition case. It intelligently combines the advantages of both flat scheduling and on-demand scheduling in such a way that the overall latency of the system is reduced. We design a suitable modeling framework to analyze the performance of the system. Simulation experiments on typical LTE systems support the performance analysis and demonstrates 10 % gains while comparing with existing eMBMS scheduling available in present LTE systems.     

Heuristic approach for broadcast scheduling,problem in wireless mesh networks

Disasters can be natural and human-initiated events that interrupt the usual functioning of people on a large scale. Region where disasters have occurred causes hazards to the public of that area and to the rescue teams. Disaster causes the damage to the communication network infrastructure also. Once the communication infrastructure is damaged, it is very difficult to the rescue teams to actively involve in relief operation. To handle these hazards, different wireless technologies can be initiated in the area of disaster. This paper discusses the innovative wireless technology for disaster management. Specifically, issues related to the broadcast scheduling problem in wireless mesh network is deployed efficiently during disaster relief are discussed. A domain specific memetic algorithm is proposed for solving the optimum time division multiple access broadcast scheduling problem in wireless mesh networks. The aim is to increase the total number of transmissions in optimized time slot with high channel utilization in a less computation time. Simulation results showed that our memetic algorithm approach to this problem achieves 100% convergence to solutions within reduced computation time while compared to recent efficient algorithms. The results were compared with several heuristic and non-heuristic algorithms for broadcast scheduling problem.     

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.     

On the efficient use of multiple channels by single‐receiver clients in wireless data broadcasting

This letter proposes an adaptive wireless push system for wireless data broadcasting environments, where multiple channels are available for broadcasting data from a broadcast server to a large number of mobile clients. We address the general case where the client demands are not dependent on client locations. The efficiency of the proposed system lies in the fact that it offers significant performance improvements to the system clients with the need of only one receiver at each client device. Copyright © 2012 John Wiley & Sons, Ltd.     

Evolved broadcast scheduling mechanism supporting energy conserving e-MBMS transmission

This study designed a data broadcasting method called evolved broadcast scheduling algorithm (eBSA) to further support LTE evolved multimedia broadcast/multicast services (e-MBMS). This eBSA provides new scheduling technology for e-MBMS and a new information searching method for user equipments that simultaneously conserves user equipment energy and maintains favorable access latency of broadcast messages. The eBSA constructs index and message channels based on the message popularities, using the index channel to guide user equipments to rapidly locate the position of the desired message in the message channel. Consequently, a short mean access time and mean turning time can be attained. The results of numerical analysis verify that when access messages possess skewed access characteristics, the proposed eBSA method performs exceptionally. Additionally, by adequately adjusting the parameter provided by the eBSA method, the optimal tradeoff between energy conservation and access latency performance can be attained.     

Graph‐based optimal asynchronous scheduling in large propagation delay underwater acoustic sensor networks

Optimal scheduling is essential to minimize the time wastage and maximize throughput in high propagation delay networks such as in underwater and satellite communication. Understanding the drawbacks of synchronous scheduling, this paper addresses an asynchronous optimal scheduling problem to minimize the time wastage during the transmission. The proposed scheduling problem is analyzed in both broadcast and non‐broadcast networks, which is highly applicable in high propagation delay networks. In broadcast networks, the proposed scheduling method reduces to a graph‐theoretic model that is shown to be equivalent to the classic algorithmic asymmetric traveling salesman problem (TSP) which is NP‐Hard. Although it is NP‐Hard, the TSP is well‐investigated with many available methods to find the best solution for up to tens of thousands of nodes. In non‐broadcast networks, the optimal solution to the scheduling problem considers the possibility of parallel transmission, which is optimized using graph coloring algorithm. The groups obtained through graph coloring are solved using Asymmetric Traveling Salesman algorithm to obtain the optimal schedule. The proposed method efficiently solves the scheduling problem for networks of practical size.     

Broadcast scheduling with MIMO links in multi-hop ad hoc networks

As the current medium access control protocols with Multiple Input Multiple Output (MIMO) links only bear point to point service, broadcast scheduling algorithm in ad hoc networks with MIMO links is proposed. The key to the proposed broadcast scheduling algorithm is the time slot scheduling algorithm which guarantees collision-free transmissions for every node and the mini- mum frame length. The proposed algorithm increases the simultaneous transmissions of MIMO links efficiently. Due to the interference null capacity of MIMO links, the interference node set of each node can decrease from two-hop neighbors to one-hop neighbors possibly. Simulation results show that our algorithm can greatly improve network capacity and decrease average packet delay.     

MU-MIMO下行链路基于关联干扰的先验式用户调度

该文针对MU-MIMO下行(广播)信道提出一种基于空间子信道关联干扰的先验式调度算法。该方法将用户调度转换为子信道的选择问题,通过综合考虑候选子信道的传输增益,以及候选者与已选的和潜在的、将来可能被选中的子信道间的相互干扰,获得一组相互干扰较小的子信道。仿真结果表明,合理地选取关联干扰参数,该算法能够获得计算复杂度与传输性能的良好折中,有效改善系统和速率。