In this paper, we present ICN-FC, which is an Information-Centric Networking (ICN) based framework for efficient functional chaining (FC). The key enabling techniques for ICN-FC includes naming semantics, Interest & Data processing and an efficient FC forwarding strategy. By using the proposed solutions, a functional chaining request, which consists of the name of raw data and an ordered set of functions, can be executed seamlessly, dynamically and flexibly in the network. In addition, the novel FC forwarding strategy can be used to improve the forwarding efficiency for functional chaining requests. The overall feasibility and efficiency of the proposed solutions are validated by using both experimental prototype and network simulation. The results show that the proposed solutions outperform previous works such as named function networking to support functional chaining applications.

In this paper, we present a method for resource allocation for small cells that integrate licensed and unlicensed RF operations motivated by the widespread WiFi hotspots and the common inclusion of WiFi interface in most cellular terminals. Small cells have proven popular for cell coverage enhancement and traffic offloading from macrocells. We formulate an optimization problem that jointly allocates resources over both licensed and unlicensed bands with the goal of maximizing sum small cell user equipment (SUE) rate while achieving fairness among these user equipments and controlling inter-cell interference to neighboring macrocell users. The proposed solution further considers the quality of service (QoS) requirement of SUE traffics to be distributed over both licensed and unlicensed bands. We show the formulation of the proposed optimization problem as an efficient and low complexity linear programming. We further show that our problem formulation can be modified to maximize the revenue of mobile network operators. Our proposed solution achieves better performance than several existing solutions.

We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme.

WiFi interfaces have been recently incorporated in most cellular user equipments (UEs). In current practice, the UE selects either the licensed band for cellular technologies or the unlicensed WiFi band depending on the signal quality of both bands. At the same time, small (pico or femto) cells have also become popular means to offload traffic from traditional macro-cell networks and to improve cell coverage. This work presents a method for dynamic switching and aggregation of licensed and unlicensed bands in small cells for traffic offloading and per-user throughput enhancement. Our proposed method allows small cells to jointly control transmission in both licensed and unlicensed bands in order to maximize the sum of small cell user throughputs over both bands while constraining the interference effect to maintain the Quality of Service (QoS) requirements for macrocell user equipments. Performance evaluation shows that our proposed scheme outperforms other existing solutions.

This work studies dual-access-technology femtocells equipped with both cellular and non-cellular air interfaces with the goal of increasing per-user throughput as well as achieving user fairness. We target enterprise environments characterized by high data rates and/or dense user terminals such as corporate premises, shopping malls, or stadiums. To meet this high data demand, multiple femtocells are deployed for which the major challenge is interference management. We propose an architecture for interference management and resource allocation over both cellular and non-cellular bands. Numerical evaluation shows that our proposed solution outperforms other existing solutions.