We present a scheduling protocol, called Time-Shift scheduling, to forward data packets from multiple input flows to a single output channel. Each input flow is guaranteed a predetermined forwarding rate and an upper bound on packet delay. The protocol is an improvement over existing protocols because it satisfies the properties of low delay, fairness, and efficiency, while existing protocols fail to satisfy at least one of these properties. In TimeShift scheduling, each flow is assigned an increasing timestamp, and the packet chosen for transmission is taken from the flow with the least timestamp. The protocol features the novel technique of time shifting, in which the scheduler's real-time clock is adjusted to prevent flow timestamps from increasing faster than the real-time clock. This bounds the difference between any pair of flow timestamps, thus ensuring the fair scheduling of flows.
As mobility became the norm rather than the exception, location-based services are playing more of a key role in assisting mobile users. In this paper, we address the challenges of providing location-based services to users in areas of sudden population increases, such as stadiums and traffic jams. A sudden increase in the number of mobile users leads to an increasing demand for the already scarce wireless bandwidth, thus causing dramatical throughput degradation and an increase in connectivity failures. We propose a hybrid model within which a peer-to-peer mode is deployed to assist the cellular-based network whenever a sudden increase in population density is sensed by the base station. Location-based data is migrated to selected elite nodes, thus allowing other peer nodes to get their information locally. This approach is proven, through experimental results, to decrease the query response time and number of query failures.
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