Load balancing solution for heterogeneous wireless networks based on the knapsack problem

Kiss, Zsuzsanna Ilona; Hosu, Andrei Ciprian; Varga, Mihaly; Polgar, Zsolt Alfred

doi:10.1109/tsp.2015.7296381

Cited by 6 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our work, we formulate the dual UA-RA problem as a MKP, which is an NP-complete optimization problem [4]. Many techniques based on dynamic programming, branchand-bound, greedy, GA, ant colony, particle swarm optimization (PSO) were employed for solving MKP [25].…”

Section: Related Workmentioning

confidence: 99%

“…To remove these ineffective solutions, the MKP items were arranged in decreasing order of their profits, i.e., the higher the profit, the lower the index. If the number of items n is greater 4 A target runner must be given to execute the target algorithm with a particular configuration and instance parameter. The target runner function (or program) serves as an interface between the target algorithm execution and irace: it receives the instance and configuration as arguments and must return the evaluation of the target algorithm's execution.…”

Section: Performance Improvementmentioning

confidence: 99%

“…( 13) indicates that each BS can serve at least one UE. OP belongs to a class of assignment problems which are proven to be combinatorial and NP-hard [4], [20], [25].…”

Section: Notationmentioning

confidence: 99%

“…We have formulated the UA-RA problem as multiple knapsack problem (MKP) in our paper, which can be broadly described as follows: Given a set of items, each of which has a weight and a value, it is essential to measure the amount of each item to be included in a knapsack so that the total weight is smaller than the capacity of the knapsack and the total value is as high as possible [4]. A collection of m knapsacks with various capacities is given in the case of the MKP.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Reduced Complexity Optimal Resource Allocation for Enhanced Video Quality in a Heterogeneous Network Environment

Agarwal

Ruffini

Muntean

2022

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

The latest Heterogeneous Network (HetNet) environments, supported by 5th generation (5G) network solutions, include small cells deployed to increase the traditional macrocell network performance. In HetNet environments, before data transmission starts, there is a user association (UA) process with a specific base station (BS). Additionally, during data transmission, diverse resource allocation (RA) schemes are employed. UA-RA solutions play a critical role in improving network load balancing, spectral performance, and energy efficiency. Although several studies have examined the joint UA-RA problem, there is no optimal strategy to address it with low complexity while also reducing the time overhead. We propose two different versions of simulated annealing (SA): Reduced Search Space SA (RS 3 A) and Performance-Improved Reduced Search Space SA (P IRS 3 A), algorithms for solving UA-RA problem in HetNets. First, the UA-RA problem is formulated as a multiple knapsack problem (MKP) with constraints on the maximum BS capacity and transport block size (TBS) index. Second, the proposed RS 3 A and P IRS 3 A are used to solve the formulated MKP. Simulation results show that the proposed scheme P IRS 3 A outperforms RS 3 A and other existing schemes such as Default Simulated Annealing (DSA), and Default Genetic Algorithm (DGA) in terms of variability and DSA and RS 3 A in terms of Quality of Service (QoS) metrics, including throughput, packet loss ratio (PLR), delay and jitter. Simulation results show that P IRS 3 A generates solutions that are very close to the optimal solution.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Performance Improvementmentioning

confidence: 99%

“…( 13) indicates that each BS can serve at least one UE. OP belongs to a class of assignment problems which are proven to be combinatorial and NP-hard [4], [20], [25].…”

Section: Notationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations