Bandwidth Allocation In Networks Research Articles

Fair Network Bandwidth Allocation in IaaS Datacenters via a Cooperative Game Approach

With wide application of virtualization technology, tenants are able to access isolated cloud services by renting the shared resources in Infrastructure-as-a-Service (IaaS) datacenters. Unlike resources such as CPU and memory, datacenter network, which relies on traditional transport-layer protocols, suffers unfairness due to a lack of virtual machine (VM)-level bandwidth guarantees. In this paper, we model the datacenter bandwidth allocation as a cooperative game, toward VM-based fairness across the datacenter with two main objectives: 1) guarantee bandwidth for VMs based on their base bandwidth requirements, and 2) share residual bandwidth in proportion to the weights of VMs. Through a bargaining game approach, we propose a bandwidth allocation algorithm, Falloc, to achieve the asymmetric Nash bargaining solution (NBS) in datacenter networks, which exactly meets our objectives. The cooperative structure of the algorithm is exploited to develop an online algorithm for practical real-world implementation. We validate Falloc with experiments under diverse scenarios and show that by adapting to different network requirements of VMs, Falloc can achieve fairness among VMs and balance the tradeoff between bandwidth guarantee and proportional bandwidth sharing. Our large-scale trace-driven simulations verify that Falloc achieves high utilization while maintaining fairness among VMs in datacenters.

A Smart Clustering Based Approach To Dynamic Bandwidth Allocation In Wireless Networks

A Smart Clustering Based Approach To Dynamic Bandwidth Allocation In Wireless Networks

Energy-Efficient Routing and Bandwidth Allocation in OFDM-Based Optical Networks

This paper introduces a novel routing and bandwidth allocation strategy for orthogonal frequency-division multiplexing (OFDM)-based elastic optical networks, aiming to optimize the network operational expenditures in terms of energy consumption. Based on the previously reported analytical bit error rate model for an OFDM-based optical transmission line, an optimization problem is formulated to allocate a set of lightpaths according to realistic network topologies, where the routing path, modulation level, bandwidth, and optical transceiver power of each lightpath are jointly determined for achieving minimum power consumption. To reduce computational complexity, a suboptimal iterative flipping method for solving the above NP-complete optimization problem is proposed, which achieves better performance than a simulated annealing scheme while consuming considerably fewer search iterations.

Utility Maximized Two-level Game-Theoretic Approach for Bandwidth Allocation in Heterogeneous Radio Access Networks

To solve the optimal bandwidth allocation problem in heterogeneous radio access networks (H-RANs), a two-level game-theoretic approach is proposed to maximize the utility of network providers and users by considering the network resource distributions and service demands. In the area-level game, the Nash equilibrium is achieved by using a noncooperative game for the bandwidth allocation in different areas to maximize network utility. Moreover, in each service area, the traffic-level bandwidth allocation and pricing approach is applied to allocate the appropriate portion of bandwidth for different networks and users using the Stackelberg game, with the network as the leader and the user as the follower. Furthermore, the Stackelberg equilibrium is achieved by an iterative algorithm in this paper. Simulation results prove that the proposed game-theoretic approaches can efficiently and significantly maximize the utility of networks and users.

Heterogeneous Network Bandwidth Allocation Method Based on the Business Characteristics

Heterogeneous Network Bandwidth Allocation Method Based on the Business Characteristics

A Bandwidth Degradation Technique to Reduce Call Dropping Probability in Mobile Network Systems

A generic video telephony may require more than 40 kbps whereas a low motion video telephony may require about 25 kbps for data transmission. From the designing point of view these requirements demands for an alternative resource planning, especially for bandwidth allocation in wireless networks. In wireless network where bandwidth is a scare resource, the system may need to block incoming user if all of the bandwidth has been used to provide highest quality of service to existing users. However this bandwidth resource planning may be unacceptable for larger application. This work aims towards a realization of a mobile network using W-CDMA multi access technique supporting multilevel quality of services. The bandwidth allocation to multiple users is adjusted dynamically according to the required network condition so as to increase bandwidth utilization. The work analyzes the performance deriving the degradation period ratio, mean degradation time and degradation state for the implemented wireless network. The proposed work is aim to implement on Matlab tool for its functional verification considering various mobility patterns.

A Bandwidth Degradation Technique to Reduce Call Dropping Probability in Mobile Network Systems

A generic video telephony may require more than 40 kbps whereas a low motion video telephony may require about 25 kbps for data transmission. From the designing point of view these requirements demands for an alternative resource planning, especially for bandwidth allocation in wireless networks. In wireless network where bandwidth is a scare resource, the system may need to block incoming user if all of the bandwidth has been used to provide highest quality of service to existing users. However this bandwidth resource planning may be unacceptable for larger application. This work aims towards a realization of a mobile network using W-CDMA multi access technique supporting multilevel quality of services. The bandwidth allocation to multiple users is adjusted dynamically according to the required network condition so as to increase bandwidth utilization. The work analyzes the performance deriving the degradation period ratio, mean degradation time and degradation state for the implemented wireless network. The proposed work is aim to implement on Matlab tool for its functional verification considering various mobility patterns. Full Text: PDF DOI: http://dx.doi.org/10.11591/telkomnika.v16i2.8426

Minimum cost maximum flow algorithm for upstream bandwidth allocation in OFDMA passive optical networks

This paper presents a minimum cost maximum flow (MCMF) based upstream bandwidth allocation algorithm, which supports differentiated QoS for orthogonal frequency division multiple access passive optical networks (OFDMA-PONs). We define a utility function as the metric to characterize the satisfaction degree of an ONU on the obtained bandwidth. The bandwidth allocation problem is then formulated as maximizing the sum of the weighted total utility functions of all ONUs. By constructing a flow network graph, we obtain the optimized bandwidth allocation using the MCMF algorithm. Simulation results show that the proposed scheme improves the performance in terms of mean packet delay, packet loss ratio and throughput.

Multi-Dimensional Bid Greedy Auction Mechanism for Bandwidth Allocation

Since current bandwidth mechanisms need communicating general functions or long convergence phase, they are not feasible in practice. In this letter, an efficient bandwidth allocation mechanism is proposed, which called Multi-dimensional Bid Greedy auction mechanism. It presents the advantage that the Multi-dimensional bid is submitted once only, saving a lot of signalization overhead. We formulate the problem of bandwidth allocation in networks as a combinatorial auction problem and propose an allocation rule to solve it. This allocation rule is complemented by a payment rule of the VCG (Vickrey-Clarke-Groves) type, which provides users with the incentive to bid truthfully, thus simplifying bidding. We argue that our mechanism is simple and applicable to real networks. Since our mechanism's computational complexity is low, it can serve as a fast and practical solution to bandwidth allocation.

Bandwidth allocation in cellular networks with multiple interferences

We study the problem of bandwidth allocation with multiple interferences. In this problem the input consists of a set of users and a set of base stations. Each user has a list of requests, each consisting of a base station, a frequency demand, and a profit that may be gained by scheduling this request. The goal is to find a maximum profit set of user requests S that satisfies the following conditions: (i) S contains at most one request per user, (ii) the frequency sets allotted to requests in S that correspond to the same base station are pairwise non-intersecting, and (iii) the QoS received by any user at any frequency is reasonable according to an interference model. In this paper we consider two variants of bandwidth allocation with multiple interferences. In the first each request specifies a demand that can be satisfied by any subset of frequencies that is large enough. In the second each request specifies a specific frequency interval. Furthermore, we consider two interference models, multiplicative and additive. We show that these problems are extremely hard to approximate if the interferences depend on both the interfered and the interfering base stations. On the other hand, we provide constant factor approximation algorithms for both variants of bandwidth allocation with multiple interferences for the case where the interferences depend only on the interfering base stations. We also consider a restrictive special case that is closely related to the Knapsack problem. We show that this special case is NP-hard and that it admits an FPTAS.

A trail multi-splitting method for throughput improvement in light trail networks

Light trail networks have been proposed as an extension of lightpath networks in order to enable sub-wavelength bandwidth allocation in WDM networks. The networks need a medium access control (MAC) method to avoid collisions of data transmissions. We have proposed a MAC method which adopts a token-passing mechanism. The method splits one trail into two trails: one upstream trail and one downstream trail and permits independent data transmissions on the trails. However, the method leaves bandwidths of links upstream from the token-holding node idle because the method only splits the original trail into two trails and leaves the upstream trail unsplit. In this paper, we propose a novel token-passing MAC method for further improving trail throughputs. Our proposed method recursively splits the upstream trail, and consequently the original trail can be split into more than two trails. In the proposed method, an appropriate setting of upstream/downstream token-holding times of all nodes is a key factor to successfully accommodate an input traffic. Therefore, we tackle a problem (called a token-holding time decision problem) where we optimize token-holding times of all nodes so that input traffic is successfully accommodated. We formulate the problem as a linear programming model. Numerical examples on maximum effective throughput show that the proposed method is more superior as the ratio of short-hop traffic is higher in input traffic patterns.

Energy-Efficient Bandwidth and Power Allocation for Multi-Homing Networks

This paper investigates resource allocation for multi-homing networks where users can simultaneously transmit data to multiple radio access networks (RANs) using multiple air interfaces. We aim at optimally assigning the bandwidth and power to each user-RAN connection so as to maximize energy-efficiency of the entire network subject to user specific QoS requirements as well as the available resource budgets. First, we study the problem of resource allocation for scenarios where the connections between the users and the RANs are predefined, which naturally leads to a fractional program. To obtain the optimal solution efficiently and facilitate distributed implementations, we further equivalently transform the design problem into a convex program using a parameter-free approach and develop a decentralized algorithm based on the alternating direction method of multipliers. Second, we investigate the problem of joint link selection and resource allocation for energy-efficiency maximization. The problem is cast as a mixed integer nonlinear convex program for which we particularize the branch and bound method to find an optimal solution. Then, two suboptimal low-complexity designs are proposed: the first one is based on greedy algorithm, which gradually maximizes the virtual link energy-efficiency; the other one is based on the concept of sparsity-inducing norm. Simulation results are presented to demonstrate the potential gains in terms of energy-efficiency of the proposed methods.

VMbuddies: Coordinating Live Migration of Multi-Tier Applications in Cloud Environments

Enabled by virtualization technologies, various multi-tier applications (such as web applications) are hosted by virtual machines (VMs) in cloud data centers. Live migration of multi-tier applications across geographically distributed data centers is important for load management, power saving, routine server maintenance and quality-of-service. Different from a single-VM migration, VMs in a multi-tier application are closely correlated, which results in a correlated VM migrations problem. Current live migration algorithms for single-VM cause significant application performance degradation because intermediate data exchange between different VMs suffers relatively low bandwidth and high latency across distributed data centers. In this paper, we design and implement a coordination system called VMbuddies for correlated VM migrations in the cloud. Particularly, we propose an adaptive network bandwidth allocation algorithm to minimize the migration cost in terms of migration completion time, network traffic and migration downtime. Experiments using a public benchmark show that VMbuddies significantly reduces the performance degradation and migration cost of multi-tier applications.

Coordinated coalition formation in throughput‐efficient cognitive radio networks

AbstractIn this paper, we consider the problem of joint coalition formation (CF) and bandwidth allocation in cognitive radio networks. We assume that the secondary links will be partitioned into disjoint coalitions, by which the available spectrum will be reused. On the other hand, we assume that the members of each coalition will transmit over orthogonal sub‐bands with the available spectrum being optimally allocated among them. We formulate the problem as a coordinated CF game, where the optimization is held at a secondary coordinator that has all the required channel information. Given these assumptions, we derive a closed‐form expression of the optimal bandwidth allocation for any given network partition, and we propose an efficient algorithm to reach a Nash‐stable partition (coalition structure), with the objective of improving the network throughput. Furthermore, we provide a probabilistic analysis of the stability of a grand structure and a singleton structure, and we employ this to obtain a lower bound on the stability of a general coalition structure (other than grand and singleton). Performance analysis shows that the proposed CF algorithm with optimal bandwidth allocation provides a substantial gain in the network throughput over existing CF techniques as well as the simple cases of singleton and grand coalitions. Copyright © 2015 John Wiley & Sons, Ltd.

Efficient and Truthful Bandwidth Allocation in Wireless Mesh Community Networks

Nowadays, the maintenance costs of wireless devices represent one of the main limitations to the deployment of wireless mesh networks (WMNs) as a means to provide Internet access in urban and rural areas. A promising solution to this issue is to let the WMN operator lease its available bandwidth to a subset of customers, forming a wireless mesh community network, in order to increase network coverage and the number of residential users it can serve. In this paper, we propose and analyze an innovative marketplace to allocate the available bandwidth of a WMN operator to those customers who are willing to pay the higher price for the requested bandwidth, which in turn can be subleased to other residential users. We formulate the allocation mechanism as a combinatorial truthful auction considering the key features of wireless multihop networks and further present a greedy algorithm that finds efficient and fair allocations even for large-scale, real scenarios while maintaining the truthfulness property. Numerical results show that the greedy algorithm represents an efficient, fair, and practical alternative to the combinatorial auction mechanism.

Convex optimization over fixed point sets of quasi-nonexpansive and nonexpansive mappings in utility-based bandwidth allocation problems with operational constraints

Network bandwidth allocation is a central issue in modern communication networks. The main objective of the bandwidth allocation is to allocate an optimal bandwidth for maximizing a predefined utility over the capacity constraints to traffic sources. When a centralized operator, which manages all the bandwidth allocations in the network, has a certain operational policy, the bandwidth allocation reflecting the operational policy should result in the network being more stable and reliable. Accordingly, we need to solve a network bandwidth allocation problem under both capacity constraints and operational constraints. To develop a novel algorithm for solving the problem, we translate the network bandwidth allocation problem into one of minimizing a convex objective function over the intersection of the fixed point sets of certain quasi-nonexpansive and nonexpansive mappings and propose a fixed point optimization algorithm for solving it. We numerically compare the proposed algorithm with the existing algorithm for solving a concrete bandwidth allocation problem and show its effectiveness.

Energy Efficient Bandwidth Allocation in Heterogeneous Wireless Networks

Wireless heterogeneous networks (HetNet) are continuing to bring the industrial networks and intelligent systems more smarter. In heterogeneous networks, energy saving is vital for a sustainable network development, which can be achieved through using various spectrum allocation schemes. It is significant that energy-efficient(EE) spectrum allocation should consider large-scale user behavior, which characterizes the macro BSs that guarantee traffic requirements in non-hotspot regions and the micro BSs that guarantee traffic requirements in hotspot regions. This paper presents four bandwidth allocation schemes for the (a) orthogonal, (b) shared, (c) shared/orthogonal frequency band allocation (SOFA) and (d) shared/orthogonal frequency band allocation under micro BSs transmit power change (SOFA-MPC), where the large-scale user behavior is taken into account. Then we give closed-form formulas of bandwidth allocation schemes which establish the quantitative relationship between the large-scale user behavior and bandwidth allocation strategy. Both theoretical and simulation results show that SOFA scheme is effective in guaranteeing both the demands of the large-scale user behavior and keeping low power consumption than orthogonal allocation scheme and shared scheme. SOFA-MPC scheme has a close relation with the large-scale user behavior too. We give the variation range of transmit power variation bias ? in all circumstances. Simulation and analytical results show that the SOFA-MPC EE is higher than the SOFA EE within the limits of ?.

QoS‐driven jointly optimal power and bandwidth allocation for heterogeneous wireless networks

By integrating the concept of effective capacity, the quality-of-service (QoS)-driven power and bandwidth allocation for heterogeneous wireless networks are investigated. The objective is to improve the power efficiency while providing delay QoS guarantees for the multi-mode mobile terminal users. First, the joint power and bandwidth allocation problem is formulated as a convex problem. Then, by solving the problem in the dual domain, an iterative algorithm to achieve the jointly optimal power and bandwidth allocation is proposed. The analytical results show that the optimal power and bandwidth allocation depends not only on the channel quality, but also on the delay QoS constraints. The numerical results verify that the proposed scheme can achieve the best power efficiency compared to the existing schemes.

Reputation-based Network Bandwidth Allocation Mechanism

Reputation-based Network Bandwidth Allocation Mechanism

PARALLEL OPTIMIZATION ALGORITHM FOR SMOOTH CONVEX OPTIMIZATION OVER FIXED POINT SETS OF QUASI-NONEXPANSIVE MAPPINGS

Smooth convex optimization problems are solved over fixed point sets of quasi-nonexpansive mappings by using a distributed optimization technique. This is done for a networked system with an operator, who manages the system, and a finite number of users, by solving the problem of minimizing the sum of the operator's and users' differentiable, convex objective functions over the intersection of the operator's and users' fixed point sets of quasi-nonexpansive mappings. Under the assumption that the operator can communicate with all users, a parallel optimization algorithm can be devised that enables the operator to find a solution to the problem without using all user objective functions and quasi-nonexpansive mappings. This algorithm does not use proximity operators, in contrast to conventional parallel proximal algorithms. Moreover, it can optimize over fixed point sets of quasi-nonexpansive mappings, in contrast to conventional fixed point algorithms. Investigation of the algorithm's convergence properties for a constant step-size rule reveals that, with a small constant step size, it approximates the solution to the problem. Consideration of the case in which the step-size sequence is diminishing demonstrates that the algorithm converges to the problem solution. Application of the algorithm to network bandwidth allocation based on an operational policy is shown to make the network more stable and reliable.