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One of the major challenges in the context of transmitting real-time multimedia data in broadband wireless access (BWA) systems is that the varied bit rate of traffic causes low bandwidth utilization. The conventional uplink scheduling algorithms for variable bit rate (VBR) video traffic transmission in IEEE 802.16 BWA systems have some disadvantages, including waste of uplink bandwidth, MAC overhead, and access delay. To cope with these difficulties, we propose an uplink scheduling algorithm for VBR traffic transmission for IEEE 802.16 BWA systems. In the proposed algorithm, the base station (BS) assigns uplink bandwidth to the video user by considering the traffic state transitions. The uplink bandwidth is equally divided into several intervals where each interval represents a traffic state. Only when the traffic state is changed, the bandwidth request process is incurred. Also, by using two reserved bits in the generic MAC header of IEEE 802.16 BWA systems as piggyback bits, the information about traffic state transition can be sent to the BS without extra overhead. Simulations conducted with QualNet 4.0 show that the bandwidth waste ratio of our proposed algorithm is less than that of the conventional algorithms. That is, the proposed algorithm outperforms the conventional algorithms for VBR traffic transmission in IEEE 802.16 BWA systems in terms of bandwidth utilization.

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Recently, many useful services have been provided through wireless mobile devices. One of the critical issues is that mobile devices are generally built with limited computing capability, and thus may not be able to handle the complexity of many advanced services. This problem can be mitigated by offloading certain jobs from the mobile devices to the edge or cloud servers. However, the locations of the edge servers and the allocation of the offloading jobs to the edge servers can significantly affect the traffic generated in the network. Accordingly, this study conducts an investigation into the edge server placement and work allocation strategy with a focus on minimizing the total traffic load so as to achieve green communications in the mobile cloud networks. Mobile devices are assumed to be attached to the nearby node and they may send work offloading requests to the attached nodes. Meanwhile, edge servers are deployed at carefully selected nodes. The offloading jobs received by a node are assigned to a selected edge server. If the edge server is busy, the work will be forwarded to the central cloud server. Otherwise, it is processed locally in the edge server. A queuing model is adopted to evaluate the job forwarding probability at the edge servers. The problem is formulated as an integer programming problem. Two novel heuristic schemes are proposed, namely the Set-by-Set algorithm and the K-clustering algorithm. The simulation results showed that the K-clustering algorithm consistently outperforms both the Set-by-Set algorithm and the Density-Based-Clustering (DBC) algorithm presented in the literature in terms of a lower total traffic load within the network. INDEX TERMS Edge computing, cloud networks, work offloading, green communications, edge server placement.