Joint Optimization of Multicast Energy in Delay-Constrained Mobile Wireless Networks - 2018


This Project studies the matter of optimizing multicast energy consumption in delay-constrained mobile wireless networks, where data from the supply desires to be delivered to all or any the k destinations among an imposed delay constraint. Most existing works merely focus on deriving transmission schemes with the minimum transmitting energy, overlooking the energy consumption at the receiver aspect. Thus, during this Project, we tend to propose ConMap, a completely unique and general framework for economical transmission theme design that jointly optimizes each the transmitting and receiving energy. In doing thus, we formulate our drawback of designing minimum energy transmission theme, called DeMEM, as a combinatorial optimization one, and prove that the approximation ratio of any polynomial time algorithm for DeMEM can't be higher than (one/4) lnk. Aiming to produce additional efficient approximation schemes, the proposed ConMap initial converts DeMEM into a similar directed Steiner tree downside through making auxiliary graph gadgets to capture energy consumption, then maps the computed tree back into a transmission theme. The advantages of ConMap are threefolded: one) Generality- ConMap exhibits sturdy applicability to a big selection of energy models; 2) Flexibility- Any algorithm designed for the matter of directed Steiner tree can be embedded into our ConMap framework to achieve totally different performance guarantees and complexities; 3) Potency- ConMap preserves the approximation ratio of the embedded Steiner tree algorithm, to which only slight overhead will be incurred. The three options are then empirically validated, with ConMap additionally yielding close to-optimal transmission schemes compared to a brute-force actual algorithm. To our best information, this is the primary work that jointly considers each the transmitting and receiving energy in the design of multicast transmission schemes in mobile wireless networks.

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