TY - JOUR
T1 - A fog-driven dynamic resource allocation technique in ultra dense femtocell networks
AU - Goudarzi, Mohammad
AU - Palaniswami, Marimuthu
AU - Buyya, Rajkumar
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/11/1
Y1 - 2019/11/1
N2 - The highly dense small cell structure filled with large number of Femtocell Base Stations (FBSs) is expected to address the increasing data demand of end users in current and upcoming generation of wireless networks. However, the large and random deployment of such devices incur severe interference which leads to significant performance degradation. To overcome this issue in the Orthogonal Frequency Division Multiple Access (OFDMA)-based femtocell networks, we propose a hierarchical technique consisting of a dynamic distributed clustering and a fog-driven resource allocation to optimize the total throughput of the network while mitigating the interference. Our fully distributed clustering method is designed so that FBSs adaptively form clusters with dynamic size based on the current status of the network and end users. Moreover, we put forward a policy-aware resource allocation method to address the intra and inter-cluster interference, which are two potential types of interference in clustering-based resource allocation techniques. Since our technique carefully considers users' demands in cluster formation, there is always sufficient resources for end users in each cluster, so that each cluster head can find a resource allocation solution, by which no intra-cluster interference occurs. Besides, we employ local fog servers situated in the proximity of clusters for monitoring and assigning a set of policies to CHs for resource allocation, by which the number of inter-cluster interference can be significantly reduced. The extensive simulation results demonstrate that our proposed hierarchical technique significantly improves total throughout, interference, user satisfaction, and fairness compared to other proposed techniques in dense and ultra-dense femtocell networks.
AB - The highly dense small cell structure filled with large number of Femtocell Base Stations (FBSs) is expected to address the increasing data demand of end users in current and upcoming generation of wireless networks. However, the large and random deployment of such devices incur severe interference which leads to significant performance degradation. To overcome this issue in the Orthogonal Frequency Division Multiple Access (OFDMA)-based femtocell networks, we propose a hierarchical technique consisting of a dynamic distributed clustering and a fog-driven resource allocation to optimize the total throughput of the network while mitigating the interference. Our fully distributed clustering method is designed so that FBSs adaptively form clusters with dynamic size based on the current status of the network and end users. Moreover, we put forward a policy-aware resource allocation method to address the intra and inter-cluster interference, which are two potential types of interference in clustering-based resource allocation techniques. Since our technique carefully considers users' demands in cluster formation, there is always sufficient resources for end users in each cluster, so that each cluster head can find a resource allocation solution, by which no intra-cluster interference occurs. Besides, we employ local fog servers situated in the proximity of clusters for monitoring and assigning a set of policies to CHs for resource allocation, by which the number of inter-cluster interference can be significantly reduced. The extensive simulation results demonstrate that our proposed hierarchical technique significantly improves total throughout, interference, user satisfaction, and fairness compared to other proposed techniques in dense and ultra-dense femtocell networks.
KW - 3GPP long term evolution (LTE)
KW - Distributed dynamic clustering
KW - Femtocell networks
KW - Fog servers
KW - Policy aware resource allocation
UR - http://www.scopus.com/inward/record.url?scp=85069870700&partnerID=8YFLogxK
U2 - 10.1016/j.jnca.2019.102407
DO - 10.1016/j.jnca.2019.102407
M3 - Article
AN - SCOPUS:85069870700
SN - 1095-8592
VL - 145
JO - Journal of Network and Computer Applications
JF - Journal of Network and Computer Applications
M1 - 102407
ER -