“…cloud, so that every cluster head owns a whole content. These cluster heads (2,4,6,7) multicast the content to their cluster members ({1,5,2,8},{10,11},{13,15},{3, 9,14}). Consequently, all the requesting MTs can receive the content quickly.…”
Section: Simulation Results and Analysismentioning
confidence: 99%
“…Thus, as a transmission mode with low energy consumption and high network throughput, cooperative content distribution is attracting more and more attention of researchers [5]- [11]. During the process of cooperative content distribution, the mobile cloud proposed in [5], [6] is introduced, which would work together with cooperation to improve the effectiveness of content distribution [6], [7].…”
Section: Introductionmentioning
confidence: 99%
“…The MTs will multicast their parts received from the BS to other MTs, so that all the MTs can receive the whole content. This scheme has a relative good fairness of energy consumption and low transmission delay, but network expansibility is bad as the instability of transmission can be caused with the increase of requesting MTs [6], [7], [9].…”
This paper addresses the problem of energy efficiency for content distribution over wireless network by introducing the mobile cloud. The base station (BSs) distributes a common content to a number of adjacent mobile terminals (MTs) with mobile-to-mobile (M2M) cooperation. A clustering formation algorithm and two schemes for content distribution are proposed in this paper. All requesting MTs are grouped into several cooperative clusters. Their cluster heads constitute a mobile cloud, in which every member can exchange information by short-range links with low-power. Only a whole content is received by some selected cluster heads by cooperation through long range (LR) links and more contents are received by other cluster heads through short range (SR) links. Then every cluster head multicast the content to its cluster members. Analysis of mathematical models and simulation results demonstrates that the proposed schemes significantly reduce the total energy consumption of MTs, while achieving a lower transmission delay.
“…cloud, so that every cluster head owns a whole content. These cluster heads (2,4,6,7) multicast the content to their cluster members ({1,5,2,8},{10,11},{13,15},{3, 9,14}). Consequently, all the requesting MTs can receive the content quickly.…”
Section: Simulation Results and Analysismentioning
confidence: 99%
“…Thus, as a transmission mode with low energy consumption and high network throughput, cooperative content distribution is attracting more and more attention of researchers [5]- [11]. During the process of cooperative content distribution, the mobile cloud proposed in [5], [6] is introduced, which would work together with cooperation to improve the effectiveness of content distribution [6], [7].…”
Section: Introductionmentioning
confidence: 99%
“…The MTs will multicast their parts received from the BS to other MTs, so that all the MTs can receive the whole content. This scheme has a relative good fairness of energy consumption and low transmission delay, but network expansibility is bad as the instability of transmission can be caused with the increase of requesting MTs [6], [7], [9].…”
This paper addresses the problem of energy efficiency for content distribution over wireless network by introducing the mobile cloud. The base station (BSs) distributes a common content to a number of adjacent mobile terminals (MTs) with mobile-to-mobile (M2M) cooperation. A clustering formation algorithm and two schemes for content distribution are proposed in this paper. All requesting MTs are grouped into several cooperative clusters. Their cluster heads constitute a mobile cloud, in which every member can exchange information by short-range links with low-power. Only a whole content is received by some selected cluster heads by cooperation through long range (LR) links and more contents are received by other cluster heads through short range (SR) links. Then every cluster head multicast the content to its cluster members. Analysis of mathematical models and simulation results demonstrates that the proposed schemes significantly reduce the total energy consumption of MTs, while achieving a lower transmission delay.
“…Hence, to reach an optimal number of D2D pairs which can communicate by reusing the resources of a selected CellUE, with respect to (9), (10) and (11) we can add a new D2D pair to the M as the list of the active D2D pairs.…”
Section: B D2d Pair Selection In Reumodementioning
In this paper, we consider downlink resource allocation of a cellular user to group of device-to-device (D2D) communication pair to enhance the overall system throughput and achieve higher spectral efficiency in mobile cloud. A mobile cloud can be defined as an opportunistic cooperative cluster of wireless devices in close proximity which are capable to communicate to other devices while preserving their connection to an overlay cellular access network (i.e., eNB), simultaneously. Thus this study considers D2D communications from a novel and wider perspective, assuming that multiple D2D communication links are simultaneously supported. We model, formulate and analyze the overall throughput of the mobile cloud as the function of distance between communication devices when the D2D pairs communicate in cellular, dedicated and reuse modes. In cellular and dedicated modes there is no severe intra-cell interference but for the reuse mode we propose an innovative and practical downlink resource allocation mechanism to coordinate the interferences and maximize the system sum-rate when several D2D pairs communicate by reusing the resources of a cellular user. In fact, the eNB as the centralized decision-maker selects a cellular user equipment (UE) and group of D2D pairs to communicate by reusing the downlink resources of the selected cellular UE while it guarantees the SINR at both the cellular and D2D receivers. Numerical results show that by exploiting the proposed mechanism we can achieve the aforementioned goals.
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