TY - JOUR
T1 - Minimum Overhead Beamforming and Resource Allocation in D2D Edge Networks
AU - Kim, Junghoon
AU - Kim, Taejoon
AU - Hashemi, Morteza
AU - Love, David J.
AU - Brinton, Christopher G.
N1 - Funding Information:
This work was supported in part by the National Science Foundation (NSF) under Grant CNS1642982, Grant CCF1816013, and Grant CNS1955561; and in part by the National Spectrum Consortium (NSC) under Grant W15QKN-15-9-1004
Publisher Copyright:
© 1993-2012 IEEE.
PY - 2022/8/1
Y1 - 2022/8/1
N2 - Device-to-device (D2D) communications is expected to be a critical enabler of distributed computing in edge networks at scale. A key challenge in providing this capability is the requirement for judicious management of the heterogeneous communication and computation resources that exist at the edge to meet processing needs. In this paper, we develop an optimization methodology that considers the network topology jointly with device and network resource allocation to minimize total D2D overhead, which we quantify in terms of time and energy required for task processing. Variables in our model include task assignment, CPU allocation, subchannel selection, and beamforming design for multiple-input multiple-output (MIMO) wireless devices. We propose two methods to solve the resulting non-convex mixed integer program: semi-exhaustive search optimization, which represents a 'best-effort' at obtaining the optimal solution, and efficient alternate optimization, which is more computationally efficient. As a component of these two methods, we develop a novel coordinated beamforming algorithm which we show obtains the optimal beamformer for a common receiver characteristic. Through numerical experiments, we find that our methodology yields substantial improvements in network overhead compared with local computation and partially optimized methods, which validates our joint optimization approach. Further, we find that the efficient alternate optimization scales well with the number of nodes, and thus can be a practical solution for D2D computing in large networks.
AB - Device-to-device (D2D) communications is expected to be a critical enabler of distributed computing in edge networks at scale. A key challenge in providing this capability is the requirement for judicious management of the heterogeneous communication and computation resources that exist at the edge to meet processing needs. In this paper, we develop an optimization methodology that considers the network topology jointly with device and network resource allocation to minimize total D2D overhead, which we quantify in terms of time and energy required for task processing. Variables in our model include task assignment, CPU allocation, subchannel selection, and beamforming design for multiple-input multiple-output (MIMO) wireless devices. We propose two methods to solve the resulting non-convex mixed integer program: semi-exhaustive search optimization, which represents a 'best-effort' at obtaining the optimal solution, and efficient alternate optimization, which is more computationally efficient. As a component of these two methods, we develop a novel coordinated beamforming algorithm which we show obtains the optimal beamformer for a common receiver characteristic. Through numerical experiments, we find that our methodology yields substantial improvements in network overhead compared with local computation and partially optimized methods, which validates our joint optimization approach. Further, we find that the efficient alternate optimization scales well with the number of nodes, and thus can be a practical solution for D2D computing in large networks.
KW - Wireless edge networks
KW - beamforming
KW - device-to-device (D2D) communications
KW - multiple-input-multiple-output (MIMO)
KW - network optimization
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U2 - 10.1109/TNET.2021.3133022
DO - 10.1109/TNET.2021.3133022
M3 - Article
AN - SCOPUS:85122328221
SN - 1063-6692
VL - 30
SP - 1454
EP - 1468
JO - IEEE/ACM Transactions on Networking
JF - IEEE/ACM Transactions on Networking
IS - 4
ER -