TY - GEN
T1 - Human enabled green IoT in 5G networks
AU - Din, Sadia
AU - Ahmad, Awais
AU - Paul, Anand
N1 - Publisher Copyright:
Copyright 2017 ACM.
PY - 2017/4/3
Y1 - 2017/4/3
N2 - Internet of Things (IoT) plays a major role in connecting the physical world with the cyber world through new services and seamless interconnection between heterogeneous devices. Such heterogeneous devices tend to generate a massive volume of Big Data. However, exploiting green schemes for IoT is still a challenge since IoT attains a large scale and becomes more multifaceted, the current trends of analyzing Big Data are not directly applicable to it. Similarly, achieving green IoT through the use of 5G also poses new challenges when it comes to transferring huge volume of data in an efficient way. To address the challenges above, this paper presents a scheme for humanenabled green IoT in 5G network. Green IoT is achieved by grouping mobile nodes in a cluster. Also, a mobility management model is designed that helps in triggering efficient handover and selecting optimal networks based on multi-criteria decision modeling. Afterward, we design a network architecture that integrates green IoT with 5G network. Moreover, the 5G network architecture is supported by proposed protocol stack, which maps Internet Protocol (IP), Medium Access Protocol (MAC), and Location identifiers (LOC). The proposed scheme is also implemented using C programming language to validate mobility model in 5G, regarding cost, energy, and Quality of Service.
AB - Internet of Things (IoT) plays a major role in connecting the physical world with the cyber world through new services and seamless interconnection between heterogeneous devices. Such heterogeneous devices tend to generate a massive volume of Big Data. However, exploiting green schemes for IoT is still a challenge since IoT attains a large scale and becomes more multifaceted, the current trends of analyzing Big Data are not directly applicable to it. Similarly, achieving green IoT through the use of 5G also poses new challenges when it comes to transferring huge volume of data in an efficient way. To address the challenges above, this paper presents a scheme for humanenabled green IoT in 5G network. Green IoT is achieved by grouping mobile nodes in a cluster. Also, a mobility management model is designed that helps in triggering efficient handover and selecting optimal networks based on multi-criteria decision modeling. Afterward, we design a network architecture that integrates green IoT with 5G network. Moreover, the 5G network architecture is supported by proposed protocol stack, which maps Internet Protocol (IP), Medium Access Protocol (MAC), and Location identifiers (LOC). The proposed scheme is also implemented using C programming language to validate mobility model in 5G, regarding cost, energy, and Quality of Service.
KW - 5G
KW - Big Data
KW - Clustering mechanism
KW - Green Internet of Things
KW - Network architecture
UR - http://www.scopus.com/inward/record.url?scp=85020875206&partnerID=8YFLogxK
U2 - 10.1145/3019612.3019689
DO - 10.1145/3019612.3019689
M3 - Conference contribution
AN - SCOPUS:85020875206
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 208
EP - 213
BT - 32nd Annual ACM Symposium on Applied Computing, SAC 2017
PB - Association for Computing Machinery
T2 - 32nd Annual ACM Symposium on Applied Computing, SAC 2017
Y2 - 4 April 2017 through 6 April 2017
ER -