Dynamic Resource Allocation Scheme Research Articles

Suppressing Epidemics in Networks Using Priority Planning

In this paper, we analyze a large class of dynamic resource allocation (DRA) strategies, named priority planning , that aim to suppress SIS epidemics taking place in a network. This is performed by distributing treatments of limited efficiency to its infected nodes, according to a priority-order precomputed offline. Under this perspective, an efficient DRA strategy for a given network can be designed by learning a proper linear arrangement of its nodes. In our theoretical analysis, we derive upper and lower bounds for the extinction time of the diffusion process that reveal the role of the maxcut of the considered linear arrangement. Accordingly, we highlight that the cutwidth , which is the minimum maxcut of all possible linear arrangements for a network, is a fundamental network property that determines the resource budget required to suppress the epidemic under priority planning. Finally, by making direct use of our theoretical results, we propose a novel and efficient DRA strategy, called maxcut minimization (MCM), which outperforms other competing strategies in our simulations, while offering desirable robustness under various noise profiles.

Self-organized Dynamic FFR Resource Allocation Scheme for LTE-Advanced Relay Based Networks

Inter-Cell Interference (ICI) from neighboring cells is a major challenge that severely degrade the performance of Orthogonal Frequency Division Multiple Access based cellular mobile systems, particularly for cell-edge users. An efficient technique to mitigate ICI is interference coordination. The most commonly Inter-Cell Interfere Coordination technique is Fractional Frequency Reuse (FFR). Furthermore in order to effectively improve cell-edge performance in terms of coverage extension and throughput, the 3rd Generation Partnership Project introduced the use of relays in Long Term Evolution-Advanced (LTE-A) networks to achieve self-backhauling of radio signals between Evolved NodeBs (eNBs) and UEs. This paper introduces a Self-Organized Dynamic FFR Resource Allocation scheme (SODRA-FFR) which dynamically allocates frequency resources to cell inner and outer regions in relay based LTE-A networks to improve cell edge performance and maximize fairness among UEs. In this scheme, the downlink frequency resources are dynamically allocated to cell inner and outer regions and the outer region frequency resources are dynamically distributed between eNB and relay stations in each cell based on coordination between neighboring eNBs and relay stations through a message passing approach over LTE-X2 interfaces. The performance of the proposed SODRA-FFR scheme without and with relays is evaluated using MATLAB simulations and compared with different combinations of frequency resources allocation to cell inner and outer regions as well as with other frequency reuse scheme (i.e., frequency reuse-1 and frequency reuse-3). The results show that the proposed SODRA-FFR scheme improves cell-edge performance and achieves high degree of fairness among UEs compared to reference resource allocation schemes. The results also show that the proposed SODRA-FFR scheme with RSs improves the fairness performance by 30 and 13 % compared to that of frequency reuse-1 and frequency reuse-3 schemes, respectively. In addition, the proposed SODRA-FFR scheme with RSs achieves 55 and 26 % increase in cell-edge throughput compared to that of frequency reuse-1 and frequency reuse-3 schemes, respectively.

Self‐organised dynamic resource allocation scheme using enhanced fractional frequency reuse in long term evolution‐advanced relay‐based networks

Inter-cell interference (ICI) from neighbouring cells is a major challenge that severely degrade the performance of cellular mobile communication systems, particularly for cell-edge users. An efficient technique to mitigate ICI is interference coordination. The most common ICI coordination technique is fractional frequency reuse (FFR). Furthermore in order to effectively improve cell-edge performance in terms of coverage extension and throughput, the third generation partnership project introduced the use of relays in long term evolution-advanced (LTE-A) networks. This paper presents a self-organized dynamic resource allocation scheme using enhanced FFR (SODRA-EFFR) which dynamically allocates resources to cell inner and outer regions in LTE-A relay-based networks. In this scheme, the downlink power and frequency resources allocation for cell inner and outer regions and the outer regions frequency resources allocation between evolved nodeBs (eNBs) and relay stations in each cell are dynamically allocated based on coordination between neighbouring eNBs and relay stations through LTE-X2 interfaces. The performance of the proposed scheme without and with relays is evaluated using MATLAB simulations and compared with different reference resource allocation schemes. Simulation results show that the proposed scheme improves cell-edge performance and achieves high degree of fairness among users’ equipment (UEs) compared with reference resource allocation schemes.

Dynamic resource allocation in TDD-based heterogeneous cloud radio access networks

To fulfill the explosive growth of network capacity, fifth generation (5G) standard has captured the attention and imagination of researchers and engineers around the world. In particular, heterogeneous cloud radio access network (H-CRAN), as a promising network paradigm in 5G system, is a hot research topic in recent years. However, the densely deployment of RRHs in H-CRAN leads to downlink/uplink traffic asymmetry and severe inter-cell interference which could seriously impair the network throughput and resource utilization. To simultaneously solve these two problems, we proposed a dynamic resource allocation (DRA) scheme for H-CRAN in TDD mode. Firstly, we design a clustering algorithm to group the RRHs into different sets. Secondly, we adopt coordinated multipoint technology to eliminate the interference in each set. Finally, we formulate the joint frame structure, power and subcarrier selection problem as a mixed strategy non-cooperative game. The simulation results are presented to validate the effectiveness of our proposed algorithm by compared with the existing work.

Dynamic femtocell resource allocation for managing inter‐tier interference in downlink of heterogeneous networks

This study investigates the downlink resource allocation problem in orthogonal frequency division multiple access heterogeneous networks consisting of macrocells and femtocells sharing the same frequency band. The focus is to devise optimised policies for femtocells' access to the shared spectrum, in terms of femtocell transmissions, in order to maximise femto-users (FUEs) sum data rate while ensuring that certain level of quality of service (QoS) for the macro-cell users in the vicinity of femtocells is provided. The optimal solution to this problem is obtained by employing the well-known dual Lagrangian method and the optimal femtocell transmit power and resource allocation solution is derived in detail. However, the optimal solution introduces high computational complexity. To this end, a heuristic solution to the problem is proposed. The algorithms to implement both optimal and efficient suboptimal schemes in a practical system are also given in detail while their complexity is compared. Simulation results show that proposed dynamic resource allocation scheme (a) ensures the macro-users QoS requirements compared with the Reuse-1 scheme, where femtocells are allowed to transmit at full power and bandwidth; (b) can maintain FUE data rates at high levels; (c) provides performance close to the optimal solution, while introducing much lower complexity.

Joint dynamic resource allocation and load balancing-cell selection in LTE-A HetNet scenarios based on Type 1 inband relay deployments

In LTE-A (long term evolution-advanced) networks, relaying is seen as a cost-effective solution to increase coverage and improve system capacity. Relays are deployed on the coverage of existing macrocells, so the resource sharing among different nodes and links and the inter-cell interference coordination (ICIC) are challenging issues that need to be addressed. In real scenarios, users are not uniformly distributed on cells, so the resource allocation has to adapt to changes in the traffic load distribution. This paper focuses on Type 1 half-duplex inband relaying. We propose a dynamic resource allocation scheme to adjust the frequency partitions to heterogeneous load conditions. In addition, we also propose a cell selection method which tries to connect users to the node that entails a better use of frequency resources, and at the same time, to guarantee the QoS requirements of users.

Utility-based efficient dynamic distributed resource allocation in buffer-aided relay-assisted OFDMA networks

In this paper, we study resource allocation in buffer-aided relay-assisted OFDMA networks. We consider utility-based stochastic optimization framework where there are constraints to be met either instantaneously or in average sense. Using the well-known Lyapunov drift-plus-penalty policy, we extract the instantaneous problem that needs to be solved in each slot to control the data admission and allocate the time slots, power, and subchannels. We propose the parameters that should be taken into account in utilizing the drift-plus-penalty policy in relay-assisted cellular networks, for providing fair data admission and satisfying the average power constraints. We introduce a low-complexity strategy for power and subchannel allocation and propose distributed and centralized algorithms to utilize it. Specifically, the proposed efficient dynamic distributed resource allocation (EDDRA) scheme is suitable for use in practice as it imposes less overhead on the system and splits the resource allocation tasks among the base station (BS) and the relays. Extensive simulation results show the effectiveness of the proposed parameters in meeting the objective and the constraints of the studied problem. We also show that the proposed EDDRA scheme has close performance to the proposed centralized one and outperforms an existing centralized scheme.

Dynamic Resource Allocation for Cooperative Spectrum Sharing in LTE Networks

Conventional spectrum sharing approaches assume that an unlicensed user accessing a licensed spectrum band autonomously operates by sensing (or detecting) the presence of the primary user, which is licensed to use the given band, with minimal coordination from the primary user. However, in this case, incorrect sensing decisions and resource allocation on the unlicensed secondary users' (SU) part can lead to undesired degradation of the primary users' performance. Therefore, there has been a recent paradigm shift to enable cooperative spectrum sharing, in which interaction is allowed between the primary and the secondary network for efficient spectrum utilization while limiting the interference experienced by a primary user. In this paper, we consider a cooperative spectrum sharing architecture in which the SU is assumed to be a cellular network. We then propose a novel fractional-frequency-reuse-based dynamic resource allocation (DRA) algorithm at the secondary (cellular) network. The joint DRA optimization involves simultaneous spectrum allocation across different base stations and then across users within a base station. It is an NP-hard problem and is prohibitively complex to solve for a large cellular network. Therefore, to reduce the complexity of the joint problem and offer a tractable solution, we formulate layered scheduling algorithms for cross-layer resource allocation. Furthermore, the feedback overhead between the layers is kept minimal. Finally, using simulations, we compare our proposed DRA scheme with other resource allocation schemes for sum system throughput, as well as for fairness in allocation. We also present the result for the case when the available primary spectrum varies over time and locations of SUs.

Multiobjective evolutionary algorithm based on multimethod with dynamic resources allocation

In the last two decades, multiobjective optimization has become main stream and various multiobjective evolutionary algorithms (MOEAs) have been suggested in the field of evolutionary computing (EC) for solving hard combinatorial and continuous multiobjective optimization problems. Most MOEAs employ single evolutionary operators such as crossover, mutation and selection for population evolution. In this paper, we suggest a multiobjective evolutionary algorithm based on multimethods (MMTD) with dynamic resource allocation for coping with continuous multi-objective optimization problems (MOPs). The suggested algorithm employs two well known population based stochastic algorithms namely MOEA/D and NSGA-II as constituent algorithms for population evolution with a dynamic resource allocation scheme. We have examined the performance of the proposed MMTD on two different MOPs test suites: the widely used ZDT problems and the recently formulated test instances for the special session on MOEAs competition of the 2009 IEEE congress on evolutionary computation (CEC’09). Experimental results obtained by the suggested MMTD are more promising than those of some state-of-the-art MOEAs in terms of the inverted generational distance (IGD)-metric on most test problems.

A Dynamic Resource Allocation Scheme for Group Paging in LTE-Advanced Networks

Group paging is one of the solutions proposed to deal with the radio access network (RAN) overload problem resulted from bursty machine-type communications (MTC) traffic in long-term evolution-advanced (LTE-A) networks. In group paging, the base station normally reserves a fixed amount of random access opportunities (RAOs) for the grouped users to perform random access (RA) during a paging access interval. However, the number of contending users is quickly decreased and thus, static allocation of RAOs is not efficient. This paper presents a dynamic resource allocation (DRA) scheme which dynamically adjusts the reserved RAOs for group paging based on the estimated number of contending users in each RA slot. Simulation results demonstrate that, compared with the traditional static allocation scheme, the proposed DRA scheme can improve the utilization of RAOs by 9% under a target access success probability constraint of 90%.

Two Timescale Joint Beamforming and Routing for Multi-Antenna D2D Networks via Stochastic Cutting Plane

This paper proposes a dynamic resource allocation scheme to exploit the mixed timescale channel state information (CSI) knowledge structure in a multi-antenna base station-assisted device-to-device (D2D) network. The short-term multi-antenna beamforming control at each transmit device is adaptive to the local real-time CSI. The long-term routing and flow control is adaptive to the global topology and the long-term global CSI statistics of the D2D network. The design objective is to maximize a network utility function subject to the average transmit power constraint, the flow balance constraints and the instantaneous physical layer capacity constraints. The mixed timescale problem can be decomposed into a short-term beamforming control problem and a long-term flow and routing control problem. Using the stochastic cutting plane, we propose a low complexity, self-learning algorithm, which converges to the global optimal solution without explicit knowledge of the channel statistics. Simulation illustrates performance gains with several baselines.

Buffer-aware adaptive resource allocation scheme in LTE transmission systems

Dynamic resource allocation scheme is a key component of 3GPP long-term evolution (LTE) for satisfying quality-of-service (QoS) requirement as well as improving the system throughput. In this paper, a buffer-aware adaptive resource allocation scheme for LTE downlink transmission is proposed for improving the overall system throughput while guaranteeing the statistic QoS and keeping certain fairness among users. Specifically, the priorities of the users’ data queues in the base station are ranked by their remaining life time or their queue overflow probability which is estimated by applying large deviation principle. An online measurement based algorithm which requires no statistical knowledge of the network conditions uses the queue priorities to dynamically allocate the resource blocks (RBs) for avoiding buffer overflow and providing statistic QoS guarantee. The simulation results show that the proposed algorithm improves the throughput and fairness while considerably reducing the average bit loss rate.

Detecting and Preventing DDoS Attacks in Cloud.

Cloud is becoming a dominant computing platform. Naturally, a question that arises is whether we can beat notorious DDoS attacks in a cloud environment. Researchers have demonstrated that the essential issue of DDoS attack and defence is resource competition between defenders and attackers. A cloud usually possesses profound resources, and has full control and dynamic allocation capability of its resources. Therefore, cloud offers us the potential to overcome DDoS attacks. However, individual cloud hosted servers are still vulnerable to DDoS attacks if they still run in the traditional way. In this paper, we propose a dynamic resource allocation strategy to counter DDoS attacks against individual cloud customers. When a DDoS attack occurs, we employ the idle resources of the cloud to clone sufficient intrusion prevention servers for the victim in order to quickly filter out attack packets and guarantee the quality of the service for benign users simultaneously. We establish a mathematical model to approximate the needs of our resource investment based on queueing theory. Through careful system analysis and real-world data set experiments, we conclude that we can defeat DDoS attacks in a cloud environment.

FHQA JDRA Schemes for Reliability and Energy Efficiency - Soft-DF-based OR-Assisted SC-FDMA

paper, we exploit the benefits of the diversity gains that arise from a cluster of opportunistic relays (ORs) and from the independently fading subcarriers of multiple users. Our goal is to improve the energy efficiency of the decodeand- forward-based OR-assisted single-carrier frequency-division multiple-access (SC-FDMA) uplink, where the direct transmission (DT) link is unavailable. We proposed two joint dynamic resource allocation (JDRA) schemes by assuming that the pilotaided channel-quality information (CQI) of all the users may be exchanged. Furthermore, we take the following two main aspects into account: 1) first-hop quality awareness (FHQA) for JDRA-aided OR and 2) buffering delay awareness in the context of interleaver-aided channel- coded systems. In addition, frequency-domain turbo equalizers are employed in both the relay and BS's receivers. Our results demonstrate that, compared to the DT benchmarker, the proposed FHQA JDRA schemes can achieve an energy reduction gain of 91% for a single-antenna base station (BS) receiver and up to 7.4% for a multiantenna BS when considering the energy consumption due to CQI exchange among relays.

Enhanced Cell Range Expansion and Radio Resource Allocation for a Better Traffic Offloading in HetNets

Cell range expansion (CRE) is a promising solution to offload macrocells' traffic and improve the radio capacity in heterogeneous network (HetNet). On the other hand, enhanced inter-cell interference coordination (eICIC) techniques are introduced in HetNets to mitigate the severe interference caused between the small cells and the macrocell. In this paper, we present a novel application of the CRE coupled with a new time and frequency domain based eICIC technique. Our approach offers a dynamic radio resource allocation scheme which takes into account the number of femtocells inside the macrocell, the femtocells' loads and the macrocell load. First, we propose a so called FT-CRE scheme which alternates the transmission of the macrocell and the femtocells offering high traffic offloading. Then, a more elaborated scheme called enhanced FT-CRE (eFT-CRE) is presented. In this scheme, the need in traffic offloading is estimated so that time and frequency resources are allocated between the macrocell and the femtocells accordingly. The performance of both proposed FT-CRE and eFT-CRE schemes is evaluated through simulations. The results showed that when FT-CRE scheme is applied, the achieved throughput of the victim macro-users served by femtocells which apply the CRE is increased by 6 times as compared to a common application of CRE technique based on time domain multiplexing eICIC only. The outage probability of these victim macro-users is also significantly decreased. More importantly, the eFT-CRE scheme reveals more effective in terms of total achieved throughput in the system, the outage probability and energy efficiency at the macrocell.

More than bin packing: Dynamic resource allocation strategies in cloud data centers

Resource allocation strategies in virtualized data centers have received considerable attention recently as they can have substantial impact on the energy efficiency of a data center. This led to new decision and control strategies with significant managerial impact for IT service providers. We focus on dynamic environments where virtual machines need to be allocated and deallocated to servers over time. Simple bin packing heuristics have been analyzed and used to place virtual machines upon arrival. However, these placement heuristics can lead to suboptimal server utilization, because they cannot consider virtual machines, which arrive in the future. We ran extensive lab experiments and simulations with different controllers and different workloads to understand which control strategies achieve high levels of energy efficiency in different workload environments. We found that combinations of placement controllers and periodic reallocations achieve the highest energy efficiency subject to predefined service levels. While the type of placement heuristic had little impact on the average server demand, the type of virtual machine resource demand estimator used for the placement decisions had a significant impact on the overall energy efficiency.

Pendekatan Teori Permainan Potensial untuk Manajemen Interferensi pada Jaringan Makro-Femto

In the present paper, a dynamic resource allocation scheme in orthogonal frequency-division multiple access (OFDMA) femtocells is proposed. In the proposed scheme, each femto base station dynamically selects the most appropriate subset of resource blocks (RBs) in a decentralized manner in order to mitigate the downlink cross- and co-tier interference. A game theoretic approach is used to model the interactions among autonomous entities, where each player attempts to maximize its own utility by choosing the best subset of RBs among the available RBs. The proposed utility function captures the cooperative behavior to manage the cross- and co-tier interference, which can be formulated as a potential game and demonstrated to converge to a Nash equilibrium. The simulation results show that the proposed scheme guarantees the convergence to Nash equilibrium and facilitates the femtocells to improve the throughput where the average 50% of user throughput above 7.3 Mbps, while minimizing the cross-tier interference to the macrocell network.

Dynamic Resource Allocation Scheme in Cloud Computing

Cloud Computing environment provisions the supply of computing resources on the basis of demand, as and when needed. It builds upon advances of virtualisation and distributed computing to support cost efficient usage of computing resources, emphasizing on resource scalability and on-demand services. It allows business outcomes to scale up and down their resources based on needs. Managing the customer demand creates the challenges of on-demand resource allocation. Virtual Machine (VM) technology has been employed for resource provisioning. It is expected that using virtualized environment will reduce the average job response time as well as executes the task according to the availability of resources. Hence VMs are allocated to the user based on characteristics of the job. Effective and dynamic utilization of the resources in cloud can help to balance the load and avoid situations like slow run of systems. This paper mainly focuses on allocation of VM to the user, based on analyzing the characteristics of the job. Main principle of this work is that low priority jobs (deadline of the job is high) should not delay the execution of high priority jobs (deadline of the job is low) and to dynamically allocate VM resources for a user job within deadline

Reduced-complexity mobile velocity estimation in correlated MIMO channels

This paper extends the existing class of autocorrelation function (ACF) based velocity estimation schemes, well-studied for single-antenna channels, to Multiple-Input Multiple-Output channels. The complexity of an intuitive extension approach, i.e. averaging individual velocity estimates from all MIMO sub-channels, increases exponentially with increasing MIMO antennas. This paper proposes two low-complexity schemes for the symmetric correlated MIMO channel with 'N' antennas. The first scheme, for a MIMO channel correlated on strictly either transmitter or receiver side, leads to complexity reduction by a factor of 'N/2'. The second scheme, for MIMO channels exhibiting correlation on both sides of the channel is a more intelligent velocity estimation scheme which allows reduction of complexity by a factor of 'N²/4'. In addition to the reduced complexity, velocity estimates obtained using both proposed schemes are more accurate than the intuitive extension approach. With 'massive MIMO' being envisioned as a reality in 5G, these schemes offer a low-complexity solution to estimate the important velocity parameter, eventually aiding diverse dynamic resource allocation schemes.

Optimal Joint Resource Allocation and Power Control in Bidirectional Relaying Networks

Cooperative relaying (CoR) and network coding (NC) are two promising techniques for improving the performance of next-generation mobile networks. In this paper, a dynamic joint resource allocation and power control scheme is proposed for bidirectional relaying in wireless mobile networks. We consider a bidirectional relaying network consisting of three nodes: user equipment (UE), base station or eNodeB (eNB), and an intermediate relay station (RS). We model the network by a two-way relay channel (TWRC) in which UE and eNB can choose between different transmission schemes: direct transmission, pure CoR (CoR scheme), or via the combination of NC and CoR (NC/CoR scheme). We first study the achievable rate regions for direct transmission, CoR, and NC/CoR and characterize them by a set of linear inequalities. We show that NC/CoR does not always achieve better performance than CoR or direct transmission in terms of achievable throughput. Therefore, we propose a hybrid transmission scheme with adaptive resource allocation to dynamically choose the best transmission strategy and the optimal resource allocation at each bidirectional transmission time frame. This is done on the basis of the system channel state information and the buffer occupancy of UE and eNB. The hybrid approach achieves the convex hull of the union of the rate regions of the direct, CoR, and NC/CoR schemes. Finally, we extend our hybrid approach by considering power control at the RS, and we use simulations to study the effect of power control in the hybrid scheme. It is shown that in both single-input-single-output and multiple-input-multiple-output systems, the hybrid scheme with joint power control and resource allocation improves the throughput and delay performance of the system considerably.