Optimal Dynamic Multicast Scheduling for Cache-Enabled Content-Centric Wireless Networks

Abstract

Abstract-Caching and multicasting at base stations are two promising approaches to support massive content delivery over wireless networks. However, existing scheduling designs do not make full use of the advantages of the two approaches. In this paper, we consider the optimal dynamic multicast scheduling to jointly minimize the average delay, power, and fetching costs for cache-enabled content-centric wireless networks. We formulate this stochastic optimization problem as an infinite horizon average cost Markov decision process (MDP). It is wellknown to be a difficult problem due to the curse of dimensionality, and there generally only exist numerical solutions. By using relative value iteration algorithm and the special structures of the request queue dynamics, we analyze the properties of the value function and the state-action cost function of the MDP for both the uniform and nonuniform channel cases. Based on these properties, we show that the optimal policy, which is adaptive to the request queue state, has a switch structure in the uniform case and a partial switch structure in the nonuniform case. Moreover, in the uniform case with two contents, we show that the switch curve is monotonically non-decreasing. Then, by exploiting these structural properties of the optimal policy, we propose two low-complexity optimal algorithms. Motivated by the switch structures of the optimal policy, to further reduce the complexity, we also propose a low-complexity suboptimal policy, which possesses similar structural properties to the optimal policy, and develop a low-complexity algorithm to compute this policy.

Cache-Assisted Hybrid Satellite-Terrestrial Backhauling for 5G Cellular Networks

“…In this direction, the works of [5], [6] investigate the users' service quality in terms of outage probability and delay for uniform channels. These works are extended to non-uniform channels in [7]. Caching is a promising approach to reduce the traffic load and can be more effective if the caching and physical layer are designed together.…”

Exploiting Caching and Multicast for 5G Wireless Networks

“…Let n * denote the area that requires the highest transmission power in a subset r ∈ R, i.e., n * = argmax n∈r P n . Then, to multicast a file to all the users in r, the power consumption required by MBS is given by [33]:…”

“…The optimal multicast scheduling policy for a given cache placement at a base station has been explored in [33]. Joint caching and broadcast scheduling policies for information delivery in conventional cellular networks (i.e., without SBSs) were presented in [56], [57].…”

Stochastic Content-Centric Multicast Scheduling for Cache-Enabled Heterogeneous Cellular Networks

“…Note that, [14] only considers the delay-insensitive services. However, many content-centric applications, such as video steaming, are delay-sensitive, and it is critical to consider delay performance in cache-enabled content-centric wireless networks [15]- [18]. In specific, the authors in [15] study coded multicasting for inelastic services (with strict deadline) in a single-cell network, and propose a computationally efficient content delivery algorithm under a given coded caching scheme.…”

“…In [17], the authors consider multicasting for inelastic services in a cacheenabled multi-cell network, and propose joint throughputoptimal caching and scheduling algorithms to maximize the service rates of the inelastic services. In our recent work [18], we consider optimal multicast scheduling to jointly minimize the average delay and service costs of elastic services (delaysensitive services but without strict deadlines) for a cache-enabled single-cell network. However, for elastic services, it remains unknown how to design optimal multicast scheduling to jointly minimize average delay and service costs for given cache placement in cache-enabled HetNets.…”