Optimizing bandwidth allocation for heterogeneous traffic in IoT

In Internet of Things (IoT), there generally exist two typical types of heterogeneous flows with different requirements: inelastic media flow (e.g., the monitoring flow) and elastic data flow (e.g., the environment info from measurement). These heterogeneous flows often coexist for sharing the limited bandwidth. Despite substantial works, a simple yet efficient approach to economically allocate bandwidth for these two types of flows is still not available. In this paper, we propose two methods to optimize the bandwidth allocation of these flows: the network-utility-maximization-based (NUM) method and the asymptotic analysis method. The NUM method provides a general solution to the optimization problem, but requires a certain computational complexity. The asymptotic analysis method delves into the inherent property of the network and explicitly expresses the solution in terms of protocol parameters and traffic requirements. Extensive simulations verify that the two methods are very accurate and can well achieve the desired objectives.     

An efficient approach for distributed dynamic channel allocation with queues for real-time and non-real-time traffic in cellular networks

We are witnessing these days a rapid growth of mobile users. Therefore, frequency spectrum must be efficiently utilized, as available frequency spectrum is limited. This paper proposes a channel allocation scheme with efficient bandwidth reservation, which initially reserves some channels for handoff calls, and later reserves the channels dynamically, based on the user mobility. The direction of user mobility may not be straight always, but the user may also go left, right or backwards. Thus, QoS can be improved, if the channel reservation is made based upon the user mobility and the location of the user. We devise here a new algorithm that deals with multiple traffic systems by modifying the existing DDCA algorithm [Krishna, P.V., Iyengar, N.Ch.S.N., 2008. Optimal channel allocation algorithm with efficient channel reservation for cellular networks. International Journal of Communication Networks and Distributed Systems 1 (1), 33-51]. This algorithm reserves more channels for hot cells, less number of channels for cold cells and an average number of channels for the medium cells. Furthermore, we maintain queues for all types of calls. We model the system by a three-dimensional Markov Chain and compute the QoS parameters in terms of the blocking probability of originating calls and the dropping probability of handoff calls. The results indicate that the proposed channel allocation scheme exhibits better performance by considering the above mentioned user mobility, type of cells, and maintaining of the queues for various traffic sources. In addition, it can be observed that our approach reduces the dropping probability by using reservation factor.     

An efficient TDMA start-up and restart synchronization approach for distributed embedded systems

A desired attribute in safety-critical embedded real-time systems is a system time and event synchronization capability on which predictable communication can be established. Focusing on bus-based communication protocols, we present a novel, efficient, and low-cost start-up and restart synchronization approach for TDMA environments. This approach utilizes information about a node's message length that forms a unique sequence to achieve synchronization such that communication overhead can be avoided. We present a fault-tolerant initial synchronization protocol with a bounded start-up time. The protocol avoids start-up collisions by deterministically postponing retries after a collision. We also present a resynchronization strategy that incorporates recovering nodes into synchronization.     

Fair and efficient dynamic bandwidth allocation for multi-application networks

The large diversity of applications and requirements posed to current network environments make the resource allocation problem difficult to work out. This paper proposes a dynamic algorithm based on weighted fair queueing (WFQ) to promote fairness (in the Rawlsian sense) and efficiency (in the Paretian sense) in the allocation of bandwidth for multi-application networks. Utility functions are used to characterize application requirements and provide the informational basis from where the algorithm operates. Aggregation techniques are employed to ensure scalability in the network core. Simulation results confirm a significant improvement of our approach over traditional bandwidth allocation algorithms (maxmin and proportional fairness). The algorithm also provides low errors (below 10% when compared to the zero-delay centralized approach) whenever response time does not exceed 1000 times the timescale involving flow arrivals and departures.     

MPEG-2 sources: exploiting source scalability for an efficient bandwidth allocation

The paper investigates efficient bandwidth allocation schemes for the transmission of MPEG-2 video traffic on high-speed networks. To this end we performed an extensive analysis of the traffic generated by an MPEG-2 encoder. Specifically, we encoded “The Sheltering Sky” movie according to the MPEG-2 standard. By the analysis of the generated traffic it results that a constant-quality transmission can be performed with a poor bandwidth utilization. In the paper we identified that the low bandwidth utilization is caused by rare high-rate periods in the codec bitstream. Hence, we identified the source scalability as a promising approach to achieve a “quasi-constant” quality transmission and an efficient bandwidth utilization. The effectiveness of this approach is evaluated in the paper via simulation. Specifically, by defining a Markovian model for an MPEG-2 scalable source we performed a set of simulation experiments which indicate that the source scalability approach significantly increases the utilization, while maintaining the quality of the video signal at the highest value for most of the time, e.g., a 50% of the network utilization with the highest quality for the 99.7% of the time.     

Heavy业务流的有效带宽及其基于测量的接纳控制算法

基于具突发性Heavy业务流的TES(Transform Expand Sample)模型,推导出一个计算Heavy业务流有效带宽的实用的公式,并由此公式求得的有效带宽,作为基于测量的接纳控制(MBAC)算法中新业务流所申请的带宽。仿真结果表明,采用该计算公式求得的有效带宽,MBAC算法可以取得更好的网络性能。     

An efficient bandwidth allocation algorithm for real-time VBR stream transmission under IEEE 802.16 wireless networks

This paper investigates variable rate control strategies for real-time multimedia variable bit rate (VBR) services over IEEE 802.16 broadband wireless networks. A data rate control mechanism is derived for the case where the uplink channel provides real-time services and the traffic rate parameter remains constant. This paper shows that the common queuing scheduling algorithms have some bandwidth allocation fairness problems for the real-time polling service (rtPS) in the MAC layer. In other words, the use of a VBR for the rtPS by a WiMAX system results in additional access latency jitter and bandwidth allocation disorder in the transmitted multimedia streams during the regular time interval polling of subscribe stations (SSs) for the contention bandwidth request period. However, the proposed scheduling algorithm solves these SSs contending with bandwidth resource allocation problems based on an extended rtPS (ertPS) of quality-of-service (QoS) pre-programming for a ranging response non-contention polling period. The adopted bandwidth allocation of max–min fairness queue scheduling uses a time constraint condition to transmit real-time multimedia VBR streaming in an IEEE 802.16 broadband wireless environment. In addition, we use the ns-2 simulation tool to compare the capacity of multimedia VBR stream and show that the proposed ertPS scheduling algorithm outperforms other rtPS scheduling algorithms.     

A new scheme for traffic estimation and resource allocation for bandwidth brokers

This paper is motivated by the concern of a multi-service network provider who plans to offer quality of service guarantees to users. A bandwidth broker acts as the resource manager for each network provider. Neighboring bandwidth brokers communicate with each other to establish inter-domain resource reservation agreements. Conventional approaches for resource allocation rely on pre-determined traffic characteristics. If allocation follows the traffic demand very tightly, the resource usage is efficient but leads to frequent modifications of the reservations. This would lead to increased inter-bandwidth-broker signaling in order to propagate the changes to all the concerned networks. Contrarily, if large cushions are allowed in the reservations, the modifications are far spaced in time but the resource usage becomes highly inefficient. In this paper, a new scheme for estimating the traffic on an inter-domain link and forecasting its capacity requirement, based on a measurement of the current usage, is proposed. The method allows an efficient resource utilization while keeping the number of reservation modifications to low values.     

BLOR: An efficient bandwidth and latency sensitive overlay routing approach for flash data dissemination

The problem of flash data dissemination refers to transmitting time‐critical data to a large group of distributed receivers in a timely manner, which widely exists in many mission‐critical applications and Web services. However, existing approaches for flash data dissemination fail to ensure the timely and efficient transmission, because of the unpredictability of the dissemination process. Overlay routing has been widely used as an efficient routing primitive for providing better end‐to‐end routing quality by detouring inefficient routing paths in the real networks. To improve the predictability of the flash data dissemination process, we propose a bandwidth and latency sensitive overlay routing approach named BLOR, by optimizing the overlay routing and avoiding inefficient paths in flash data dissemination. BLOR tries to select optimal routing paths in terms of network latency, bandwidth capacity, and available bandwidth in nature, which has never been studied before. Additionally, a location‐aware unstructured overlay topology construction algorithm, an unbiased top‐k dominance model, and an efficient semi‐distributed information management strategy are proposed to assist the routing optimization of BLOR. Extensive experiments have been conducted to verify the effectiveness and efficiency of the proposals with real‐world data sets. Copyright © 2014 John Wiley & Sons, Ltd.     

An efficient heuristic algorithm for selecting projects

Consider the problem of selecting a set of projects from a large number of available projects such that at least some specified levels of benefits of various types are realized at a minimum cost. This problem can be formulated in terms of the well-known 0–1 multi-dimensional knapsack problem, a special case of the general integer programming problems. In view of the NP-completeness of these problems, this paper proposes a polynomially bounded and efficient heuristic algorithm for its solution. The proposed algorithm proceeds as follows: an initial selection is found by prioritizing the projects according to a computed discard index. This initial selection set is then altered to reduce total costs by using project exchange operations. Computational results indicate that the proposed algorithm is quite effective in finding optimal or near optimal solutions.     

An efficient cluster-based CDMA/TDMA scheme for wireless mobile ad-hoc networks: A learning automata approach

In this paper, we design a dynamic frame length CDMA/TDMA scheme for clustered wireless ad hoc networks with unknown traffic parameters. In this scheme, the collision-free intra-cluster communications are organized by the cluster-heads using a TDMA scheme, and a CDMA scheme is overlaid on the TDMA to organize the interference-free inter-cluster communications. Therefore, to design such a scheme, we encounter three important problems, namely cluster formation, code assignment, and slot assignment. In this paper, we propose three algorithms to solve the addressed problems based on learning automata. In our scheme, by the proposed clustering algorithm, the wireless hosts are grouped into non-overlapping clusters. Then, by the proposed code assignment algorithm (considering the concept of code spatial reuse), an interference-free code is assigned to each cluster. Finally, by the slot assignment algorithm, each cluster member is assigned a fraction of TDMA frame proportional to its traffic load. The simulation results show that the proposed CDMA/TDMA scheme outperforms the existing methods in terms of almost all metrics of interest, specifically, under bursty traffic conditions.     

An efficient heuristic algorithm for rectangle-packing problem

Rectangle-packing problem involves many industrial applications, such as shipping, timber cutting, very large scale integration (VLSI) floor planning, and so on. This problem has shown to be NP hard, and many algorithms such as genetic algorithm, simulated annealing and other heuristic algorithms are presented to solve it. Based on the wisdom and experience of human being, an efficient heuristic algorithm is proposed in this paper. Two group benchmarks are used to test the performance of the produced algorithm, 19 instances of first group and 3 instances of second group having achieved optimal solutions. The experimental results demonstrate that the presented algorithm is rather efficient for solving the rectangle-packing problem.     

An efficient broadcast scheduling algorithm for TDMA ad-hoc networks

In this paper, we propose an efficient algorithm to find a collision-free time slot schedule in a time division multiple access frame. In order to minimize the system delay, the optimal schedule must be defined as the one that has the minimum frame length and provides the maximum slot utilization. The proposed algorithm is based on the sequential vertex coloring algorithm. Numerical examples and comparisons with the algorithm in previous research have shown that the proposed algorithm can find near-optimal solutions in respect of the system delay.Scope and purposeAn ad-hoc network was introduced in order to apply packet switching communication to a shared radio channel. Using a radio channel as the broadcast medium to interconnect users, an ad-hoc network provides flexible data communication services among a large number of geographically distributed, possibly mobile, radio units. In an ad-hoc network, since all users share a single channel by multiple access protocol, unconstrained transmission may lead to the time overlap of two or more packet receptions, called collision, resulting in damaged useless packets at the destination. Collided packets increase the system delay because they must be retransmitted. Therefore, the transmission for each station must be scheduled to avoid any collision, that is, collision-free transmission should be guaranteed. The time division multiple access (TDMA) technology can be used to schedule collision-free transmission. In this paper, we propose an efficient algorithm to find a collision-free time slot schedule in a TDMA ad-hoc network.     

An efficient algorithm for group multicast routing with bandwidth reservation

Multicasting refers to the transmission of data from a source node to multiple destination nodes in a network. Group multicasting is a generalisation of multicasting whereby every member of a group is allowed to multicast messages to other members that belong to the same group. The routing problem in this case involves the construction of a set of low cost multicast trees with bandwidth requirements, one for each member of the group, for multicasting messages to other members of the group. In this paper, we propose a new heuristic algorithm to generate a set of low cost multicast trees with bandwidth requirements. Simulation results show that our proposed algorithm performed better in terms of cost and in terms of utilisation of bandwidth as compared to an existing algorithm that was proposed by Jia and Wang [3].     

A pricing approach for bandwidth allocation in differentiated service networks

We present a decentralized auction-based scheme for bandwidth allocation and pricing in a differentiated service-based network. Different classes of clients provide their own expected bandwidth price and required amount of bandwidth. A service provider decides the admission price and differentiated service provided for each class of clients. We introduce mathematical formulations and provide a solution approach to maximize the service provider's revenue. For a single bottleneck link case, a polynomial-time algorithm is developed to obtain an optimal solution. For a multiple bottleneck link case, a heuristic algorithm is developed to solve the problem. The effectiveness of our solution approach is validated by simulation results, which compare our algorithms against the traditional flat-rate pricing approach.     

An efficient placement heuristic for three-dimensional rectangular packing

By embodying the spirit of “gold corner, silver side and strawy void” directly on the candidate packing place such that the searching space is reduced considerably, and by utilizing the characteristic of weakly heterogeneous problems that many items are in the same size, a fit degree algorithm (FDA) is proposed for solving a classical 3D rectangular packing problem, container loading problem. Experiments show that FDA works well on the complete set of 1500 instances proposed by Bischoff, Ratcliff and Davies. Especially for the 800 difficult strongly heterogeneous instances among them, FDA outperforms other algorithms with an average volume utilization of 91.91%, which to our knowledge is 0.45% higher than current best result just reported in 2010.     

An efficient heuristic for reliability design optimization problems

This paper develops an efficient heuristic to solve two typical combinatorial optimization problems frequently met when designing highly reliable systems. The first one is the redundancy allocation problem (RAP) of series-parallel binary-state systems. The design goal of the RAP is to select the optimal combination of elements and redundancy levels to maximize system reliability subject to the system budget and to the system weight. The second problem is the expansion-scheduling problem (ESP) of multi-state series-parallel systems. In this problem, the study period is divided into several stages. At each stage, the demand is represented as a piecewise cumulative load curve. During the system lifetime, the demand can increase and the total productivity may become insufficient to assume the demand. To increase the total system productivity, elements are added to the existing system. The objective in the ESP is to minimize the sum of costs of the investments over the study period while satisfying availability constraints at each stage. The heuristic approach developed to solve the RAP and the ESP is based on a combination of space partitioning, genetic algorithms (GA) and tabu search (TS). After dividing the search space into a set of disjoint subsets, this approach uses GA to select the subspaces, and applies TS to each selected subspace. Numerical results for the test problems from previous research are reported and compared. The results show the advantages of the proposed approach for solving both problems.     

Hybrid P2P traffic classification with heuristic rules and machine learning

Peer-to-peer (P2P) applications have become more and more popular in recent years. Although they make our lives easier, increasing P2P traffic leads to many problems in management and security. Classifying P2P traffic accurately is becoming more critical for network management and P2P malware detection. Many methods have been proposed for P2P traffic classification, such as port-based, signature-based, pattern-based, and statistics-based methods. However, with the development of anti-identification techniques from port disguise to payload encryption or even packet size controlling, a single method is not enough to classify P2P traffic accurately. In this paper, an improved two-step hybrid P2P traffic classifier is proposed. The first step is a signature-based classifier at the packet-level combined with connection heuristics. The second step consists of a statistics-based classifier and pattern heuristics, and classifies the remaining unknown traffic at the flow level. Based on the analysis of various machine learning algorithms, the statistics-based classifier is implemented with REPTree, a decision tree algorithm. Through verification with real datasets, it is shown that our hybrid scheme provides high accuracy and low overhead compared to other hybrid schemes.