Haipeng Yao

A Survey of Mobile Information-Centric Networking: Research Issues and Challenges

To better cope with the Internet usage shift from host-centric end-to-end communication to receiver-driven content retrieval, innovative information-centric networking (ICN) architectures have been proposed. With the explosive increase in global network traffic, the energy efficiency issue in ICN is a growing concern. A number of approaches have been proposed to address the energy-efficiency issue in ICN. However, several significant research challenges remain to be addressed before its widespread deployment, including shutdown, slowdown, mobility, and cloud computing. In this paper, we present a brief survey on some of the works that have been already done to achieve green ICN and discuss some research issues and challenges. We identify several important aspects of green ICN, i.e., overview, energy efficiency metrics, network planning, enabling technologies, and challenges. Finally, we explore some broader perspectives for green ICN.

Big Data Analytics in Mobile Cellular Networks

Mobile cellular networks have become both the generators and carriers of massive data. Big data analytics can improve the performance of mobile cellular networks and maximize the revenue of operators. In this paper, we introduce a unified data model based on the random matrix theory and machine learning. Then, we present an architectural framework for applying the big data analytics in the mobile cellular networks. Moreover, we describe several illustrative examples, including big signaling data, big traffic data, big location data, big radio waveforms data, and big heterogeneous data, in mobile cellular networks. Finally, we discuss a number of open research challenges of the big data analytics in the mobile cellular networks.

Virtual Resource Allocation in Information-Centric Wireless Networks with Virtualization

Wireless network virtualization and information-centric networking (ICN) are two promising technologies in next-generation wireless networks. Traditionally, these two technologies have been addressed separately. In this paper, we show that jointly considering wireless network virtualization and ICN is necessary. Specifically, we propose an information-centric wireless network virtualization framework for enabling wireless network virtualization and ICN. Then, we formulate the virtual resource allocation and in-network caching strategy as an optimization problem, considering not only the revenue earned by serving the end users but the cost-of-leasing infrastructure as well. In addition, with recent advances in distributed convex optimization, we develop an efficient alternating direction method of multipliers (ADMM)-based distributed virtual resource allocation and in-network caching scheme. Simulation results are presented to show the effectiveness of the proposed scheme.

A multicontroller load balancing approach in software-defined wireless networks

Software-defined networking (SDN) is currently seen as one of the most promising future network technologies, which can realize the separation between control and data planes. Furthermore, the increasing complexity in future wireless networks (i.e., 5G, wireless sensor networks) renders the control and coordination of networks a challenging task. Future wireless networks need good separation of control and data planes and call for SDN method to handle the explosive increase of mobile data traffic. Relying on a single controller in future wireless networks imposes a potential scalability problem. To tackle this problem, the thought of using multiple controllers to manage the large wide-area wireless network has been proposed, where the load balance problem of multicontroller needs to be resolved. In this paper, we propose a multicontroller load balancing approach called HybridFlow in software-defined wireless networks, which adopts the method of distribution and centralization and designs a double threshold approach to evenly allocate the load. Simulation results reveal that the proposed approach can significantly relieve the working load on the super controller and reduces the load jitter of multicontroller load in a single cluster compared with the BalanceFlow method.

Virtual Network Embedding Based on the Degree and Clustering Coefficient Information

The issue of virtual network (VN) embedding constitutes an important aspect of network virtualization, which is considered to be one of the most crucial techniques to overcome the Internet ossification problem. The main purpose of VN embedding is to efficiently utilize the limited physical network resources to offer the supporting of virtual nodes and virtual links from the VNs. Due to the fact that the VN embedding problem is proved to be NP-hard, previous works have put forward some of heuristic algorithms to solve this VN embedding problem. However, most of the existing research works only consider the local resources of nodes, ignoring the topological attributes of its neighborhood nodes, and lead to lower resource utilization of the substrate network. To address this issue, we proposed an approach of VN embedding algorithm called VNE-DCC, which based on the node degree and the clustering coefficient information, we adopted the technique of node importance metric to rank the substrate nodes aim to select the node with the most embedding potential for every virtual node in each VN requests, and exploited the breadth-first-search algorithm to embed the virtual nodes aiming at reducing the resource utilization of substrate links so as to increase the acceptance ratio of VN requests and increase the revenues of operational providers. Extensive simulations have shown that the efficiency of our algorithm is better than the other state-of-the-art algorithms in terms of Revenue/Cost ratio and acceptance ratio.

DaVe: Offloading Delay-Tolerant Data Traffic to Connected Vehicle Networks

The promising connected vehicle technologies will enable a huge network of roadside units (RSUs) and vehicles equipped with communication, computing, storage, and positioning devices. Current research on connected vehicle networks focuses on delivering the data generated from or required by the vehicle networks themselves, of which the data traffic is light; thus, the vehicle-network resource utilization efficiency is low. On the other hand, a large amount of delay-tolerant traffic in other data networks consumes significant communication resources. In this paper, we introduce a new architecture of DaVe to utilize efficiently the potential resource from connected vehicles and to mitigate the congestion problem in other data networks. Delay-tolerant data traffic is offloaded from the data networks to the connected vehicle networks without extra infrastructure/hardware deployment. An optimal distributed data hopping mechanism is also proposed to enable delay-tolerant data routing over connected vehicle networks. We formulate the next-hop decision optimization problem as a partially observable Markov decision process (POMDP) and propose a heuristic algorithm to reduce computational complexity. Extensive simulation results are also presented to demonstrate the significant performance improvement of the proposed scheme.

Random Access and Virtual Resource Allocation in Software-Defined Cellular Networks With Machine-to-Machine Communications

Machine-to-machine (M2M) communications have attracted great attention from both academia and industry. In this paper, with recent advances in wireless network virtualization and software-defined networking (SDN), we propose a novel framework for M2M communications in software-defined cellular networks with wireless network virtualization. In the proposed framework, according to different functions and quality-of-service (QoS) requirements of machine-type communication devices, a hypervisor enables the virtualization of the physical M2M network, which is abstracted and sliced into multiple virtual M2M networks. In addition, we develop a decision-theoretic approach to optimize the random access process of M2M communications. Furthermore, we develop a feedback and control loop to dynamically adjust the number of resource blocks that are used in the random access phase in a virtual M2M network by the SDN controller. Extensive simulation results with different system parameters are presented to show the performance of the proposed scheme.

Modeling energy-delay tradeoffs in single base station with cache

With the explosive increase of mobile data traffic, the energy efficiency issue in cellular networks is a growing concern. Recently, the advantages of in-network caching in Internet have been widely investigated, for example, speeding up content distribution and improving network resource utilization. In this paper, we analyze the energy-delay tradeoff problem in the context of single base station (BS), which has a cache capacity to buffer the contents through it. Although additional power is consumed by the cache, work load of BS and network delay will be improved, which makes a tradeoff between network power consumption and delay. Simulation results reveal that, by introducing the cache in a BS, the network power and delay can be obviously reduced in different network conditions compared to the scenario without a cache. In addition, we find that a large cache size does not always mean a less network cost because of the more cache power consumption.

virtual network embedding based on computing, network and storage resource constraints

Network virtualization can offer more flexibility and better maintainability for the current Internet through allowing multiple heterogeneous virtual networks (VNs) to share the network resource of a common infrastructure provider. The main challenge in this respect is the efficient embedding the virtual nodes and virtual links from the VN requests onto the limited substrate network resources. The notion of storage resource can exchange bandwidth resource to some extent gives us a hint that the efficient utilization of storage resource can relieve the bandwidth resource consumption. The existing VN embedding model does not consider the storage resource constraints on substrate nodes and virtual nodes, and does not keep up with the need of actual situation. In this paper, we propose a novel VN embedding model based on 3-D resource constraints including computing, network and storage, and devise two heuristic algorithms as the baseline algorithms to deal with the VN embedding problem. To our best of our knowledge, this is the first time to propose VN embedding problem based on 3-D resources including computing, network, and storage.

An Optimal Routing Algorithm in Service Customized 5G Networks

With the widespread use of Internet, the scale of mobile data traffic grows explosively, which makes 5G networks in cellular networks become a growing concern. Recently, the ideas related to future network, for example, Software Defined Networking (SDN), Content-Centric Networking (CCN), and Big Data, have drawn more and more attention. In this paper, we propose a service-customized 5G network architecture by introducing the ideas of separation between control plane and data plane, in-network caching, and Big Data processing and analysis to resolve the problems traditional cellular radio networks face. Moreover, we design an optimal routing algorithm for this architecture, which can minimize average response hops in the network. Simulation results reveal that, by introducing the cache, the network performance can be obviously improved in different network conditions compared to the scenario without a cache. In addition, we explore the change of cache hit rate and average response hops under different cache replacement policies, cache sizes, content popularity, and network topologies, respectively.