Joint User Association and Fair Scheduling for Dual Connectivity Heterogeneous Networks

Heterogeneous small cell network is one of the most effective solutions to overcome spectrum scarcity for the next generation of mobile networks.Dual connectivity(DC)can improve the throughput for each individual user by allowing concurrent access to two heterogeneous radio networks.In this paper,we propose a joint user association and fair scheduling algorithm(JUAFS)to deal with the resource allocation and load balancing issues for DC heterogeneous small cell networks.Considering different coverage sizes,numbers of users,and quality of experience characteristics of heterogeneous cells,we present a proportional fair scheduling for user association among cells and utilize interference graph to minimize the transmission conflict probability.Simulation results show the performance improvement of the proposed algorithm in spectrum efficiency and fairness comparing to the existing schemes.

Performance Improvement through Novel Adaptive Node and Container Aware Scheduler with Resource Availability Control in Hadoop YARN

The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs.This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator(YARN)scheduler,called the Adaptive Node and Container Aware Scheduler(ANACRAC),that aligns cluster resources to the demands of the applications in the real world.The approach performs to leverage the user-provided configurations as a unique design to apportion nodes,or containers within the nodes,to application thresholds.Additionally,it provides the flexibility to the applications for selecting and choosing which node’s resources they want to manage and adds limits to prevent threshold breaches by adding additional jobs as needed.Node or container awareness can be utilized individually or in combination to increase efficiency.On top of this,the resource availability within the node and containers can also be investigated.This paper also focuses on the elasticity of the containers and self-adaptiveness depending on the job type.The results proved that 15%–20%performance improvement was achieved compared with the node and container awareness feature of the ANACRAC.It has been validated that this ANACRAC scheduler demonstrates a 70%–90%performance improvement compared with the default Fair scheduler.Experimental results also demonstrated the success of the enhancement and a performance improvement in the range of 60%to 200%when applications were connected with external interfaces and high workloads.

Joint relay selection and power allocation algorithm in two-way relay networks with proportional fair constraint

In this paper, we consider the joint relay selection and power allocation problem for two-way relay systems with multiple relay nodes. Traditionally, relay selection schemes are primarily focused on selecting one relay node to maximize the transmission sum rate or minimize the outage probability. If so, it is possible to cause certain relay nodes overloaded. In addition, the joint relay selection and power allocation problem is a mixed integer program problem and prohibitive in terms of complexity. Therefore, we propose a novel low complexity joint relay selection and power allocation algorithm with proportional fair scheduling to get the load-balancing among potential relays. Simulation results turn out that, compared with round-robin schemes and max sum rate schemes, the proposed algorithm can achieve the tradeoff between system transmission sum rate and load-balancing.

Cross-layer packet scheduling for downlink multiuser OFDM systems

This paper proposes a channel and queue aware fair （CQAF） packet scheduling scheme for the downlink packet transmission in multiuser orthogonal frequency division multiplexing （OFDM） systems. By making use of the information on the channel conditions and the queue lengths, the proposed CQAF packet scheduling scheme efficiently allocates the subcarriers, transmission power and modulation level to users under the constraints of total transmission power, the number of subcarriers, bit-error-rate （BER） requirement and generalized processor sharing （GPS）-based fairness requirement. The numerical results show that the proposed CQAF packet scheduling scheme can reduce the transmission delay and queue length significantly while maximizing system throughput and maintaining fairness among users.

Improved resource allocation strategy in SU-CoMP network

Coordinated multi-point transmission and reception （CoMP） for single user, named as SU-CoMP, is considered as an efficient approach to mitigate inter-cell interference in orthogonal frequency division multiple access （OFDMA） systems. Two prevalent approaches in SU-CoMP are coordinated scheduling （CS） and joint processing （JP）. Although JP in SU-CoMP has been proved to achieve a great link performance improvement for the cell-edge user, efficient resource allocation （RA） on the system level is quite needed. However, so far limited work has been done considering JP, and most existing schemes achieved the improvement of cell-edge performance at cost of the cell-average performance degradation compared to the single cell RA. In this paper, a two-phase strategy is proposed for SU-CoMP networks. CS and JP are combined to improve both cell-edge and cell-average performance. Compared to the single cell RA, simulation results demonstrate that, the proposed strategy leads to both higher cell-average and cell-edge throughput.