Aqua Computing: Coupling Computing and Communications

The authors introduce a new vision for providing computing services for connected devices. It is based on the key concept that future computing resources will be coupled with communication resources, for enhancing user experience of the connected users, and also for optimising resources in the providers' infrastructures. Such coupling is achieved by Joint/Cooperative resource allocation algorithms, by integrating computing and communication services and by integrating hardware in networks. Such type of computing, by which computing services are not delivered independently but dependent of networking services, is named Aqua Computing. The authors see Aqua Computing as a novel approach for delivering computing resources to end devices, where computing power of the devices are enhanced automatically once they are connected to an Aqua Computing enabled network. The process of resource coupling is named computation dissolving. Then, an Aqua Computing architecture is proposed for mobile edge networks, in which computing and wireless networking resources are allocated jointly or cooperatively by a Mobile Cloud Controller, for the benefit of the end-users and/or for the benefit of the service providers. Finally, a working prototype of the system is shown and the gathered results show the performance of the Aqua Computing prototype.Comment: A shorter version of this paper will be submitted to an IEEE magazin

A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

As the explosive growth of smart devices and the advent of many new applications, traffic volume has been growing exponentially. The traditional centralized network architecture cannot accommodate such user demands due to heavy burden on the backhaul links and long latency. Therefore, new architectures which bring network functions and contents to the network edge are proposed, i.e., mobile edge computing and caching. Mobile edge networks provide cloud computing and caching capabilities at the edge of cellular networks. In this survey, we make an exhaustive review on the state-of-the-art research efforts on mobile edge networks. We first give an overview of mobile edge networks including definition, architecture and advantages. Next, a comprehensive survey of issues on computing, caching and communication techniques at the network edge is presented respectively. The applications and use cases of mobile edge networks are discussed. Subsequently, the key enablers of mobile edge networks such as cloud technology, SDN/NFV and smart devices are discussed. Finally, open research challenges and future directions are presented as well

Cooperative Caching based on File Popularity Ranking in Delay Tolerant Networks

Increasing storage sizes and WiFi/Bluetooth capabilities of mobile devices have made them a good platform for opportunistic content sharing. In this work we propose a network model to study this in a setting with two characteristics: 1. delay tolerant; 2. lack of infrastructure. Mobile users generate requests and opportunistically download from other users they meet, via Bluetooth or WiFi. The difference in popularity of different web content induces a non-uniform request distribution, which is usually a Zipf's law distribution. We evaluate the performance of different caching schemes and derive the optimal scheme using convex optimization techniques. The optimal solution is found efficiently using a binary search method. It is shown that as the network mobility increases, the performance of the optimal scheme far exceeds the traditional caching scheme. To the best of our knowledge, our work is the first to consider popularity ranking in performance evaluation.Comment: 6 pages, 2 figures, ExtremeCom 201

Energy Efficiency in Multicast Multihop D2D Networks

As the demand of mobile devices (MDs) for data services is explosively increasing, traditional offloading in the cellular networks is facing the contradiction of energy efficiency and quality of service. Device-to-device (D2D) communication is considered as an effective solution. This work investigates a scenario where the MDs have the same demand for common content and they cooperate to deliver it using multicast multihop relaying. We focus on the problem of total power minimization by grouping the MDs in multihop D2D networks, while maintaining the minimum rate requirement of each MD. As the problem is shown to be NP-complete and the optimal solution can not be found efficiently, two greedy algorithms are proposed to solve this problem in polynomial time. Simulation results demonstrate that lots of power can be saved in the content delivery situation using multihop D2D communication, and the proposed algorithms are suitable for different situations with different advantages.Comment: To appear in IEEE/CIC ICCC 201

Content Retrieval At the Edge: A Social-aware and Named Data Cooperative Framework

Recent years with the popularity of mobile devices have witnessed an explosive growth of mobile multimedia contents which dominate more than 50\% of mobile data traffic. This significant growth poses a severe challenge for future cellular networks. As a promising approach to overcome the challenge, we advocate Content Retrieval At the Edge, a content-centric cooperative service paradigm via device-to-device (D2D) communications to reduce cellular traffic volume in mobile networks. By leveraging the Named Data Networking (NDN) principle, we propose sNDN, a social-aware named data framework to achieve efficient cooperative content retrieval. Specifically, sNDN introduces Friendship Circle by grouping a user with her close friends of both high mobility similarity and high content similarity. We construct NDN routing tables conditioned on Friendship Circle encounter frequency to navigate a content request and a content reply packet between Friendship Circles, and leverage social properties in Friendship Circle to search for the final target as inner-Friendship Circle routing. The evaluation results demonstrate that sNDN can save cellular capacity greatly and outperform other content retrieval schemes significantly.Comment: Lingjun Pu, Xu Chen, Jingdong Xu, and Xiaoming Fu, "Content Retrieval At the Edge: A Social-aware and Named Data Cooperative Framework," accepted by IEEE Transactions on Emerging Topics in Computing, 201

Towards A Marketplace for Mobile Content: Dynamic Pricing and Proactive Caching

In this work, we investigate the profit maximization problem for a wireless network carrier and the payment minimization for end-users. Motivated by recent findings on proactive resource allocation, we focus on the scenario whereby end-users who are equipped with device-to-device (D2D)communication can harness predictable demand in proactive data contents caching and the possibility of trading their proactive downloads to minimize their expected payments. The carrier, on the other hand, utilizes a dynamic pricing scheme to differentiate between off-peak and peak time prices and applies commissions on each trading process to further maximize its profit. A novel marketplace that is based on risk sharing between end-users is proposed where the tension between carrier and end-users is formulated as a Stackelberg game. The existence and uniqueness of the non-cooperative sub-game Nash equilibrium is shown. Furthermore, we explore the equilibrium points for the case when the D2D is available and when it is not available, and study the impact of the uncertainty of users future demands on the system's performance. In particular, we compare the new equilibrium with the baseline scenario of flat pricing. Despite end-users connectivity with each other, the uncertainty of their future demands, and the freshness of the pre-cached contents, we characterize a new equilibrium region which yields to a win-win situation with respect to the baseline equilibrium. We show that end-users activity patterns can be harnessed to maximize the carrier's profit while minimizing the end-users expected payments.Comment: 31 page

Air-Ground Integrated Mobile Edge Networks: Architecture, Challenges and Opportunities

The ever-increasing mobile data demands have posed significant challenges in the current radio access networks, while the emerging computation-heavy Internet of things (IoT) applications with varied requirements demand more flexibility and resilience from the cloud/edge computing architecture. In this article, to address the issues, we propose a novel air-ground integrated mobile edge network (AGMEN), where UAVs are flexibly deployed and scheduled, and assist the communication, caching, and computing of the edge network. In specific, we present the detailed architecture of AGMEN, and investigate the benefits and application scenarios of drone-cells, and UAV-assisted edge caching and computing. Furthermore, the challenging issues in AGMEN are discussed, and potential research directions are highlighted.Comment: Accepted by IEEE Communications Magazine. 5 figure

Offloading on the Edge: Analysis and Optimization of Local Data Storage and Offloading in HetNets

The rapid increase in data traffic demand has overloaded existing cellular networks. Planned upgrades in the communication architecture (e.g. LTE), while helpful, are not expected to suffice to keep up with demand. As a result, extensive densification through small cells, caching content closer to or even at the device, and device-to-device (D2D) communications are seen as necessary components for future heterogeneous cellular networks to withstand the data crunch. Nevertheless, these options imply new CAPEX and OPEX costs, extensive backhaul support, contract plan incentives for D2D, and a number of interesting tradeoffs arise for the operator. In this paper, we propose an analytical model to explore how much local storage and communication through "edge" nodes could help offload traffic in various heterogeneous network (HetNet) setups and levels of user tolerance to delays. We then use this model to optimize the storage allocation and access mode of different contents as a tradeoff between user satisfaction and cost to the operator. Finally, we validate our findings through realistic simulations and show that considerable amounts of traffic can be offloaded even under moderate densification levels

All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey

With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices. IoT is expected to connect billions of devices and humans to bring promising advantages for us. With this growth, fog computing, along with its related edge computing paradigms, such as multi-access edge computing (MEC) and cloudlet, are seen as promising solutions for handling the large volume of security-critical and time-sensitive data that is being produced by the IoT. In this paper, we first provide a tutorial on fog computing and its related computing paradigms, including their similarities and differences. Next, we provide a taxonomy of research topics in fog computing, and through a comprehensive survey, we summarize and categorize the efforts on fog computing and its related computing paradigms. Finally, we provide challenges and future directions for research in fog computing.Comment: 48 pages, 7 tables, 11 figures, 450 references. The data (categories and features/objectives of the papers) of this survey are now available publicly. Accepted by Elsevier Journal of Systems Architectur

AACT: Application-Aware Cooperative Time Allocation for Internet of Things

As the number of Internet of Things (IoT) devices keeps increasing, data is required to be communicated and processed by these devices at unprecedented rates. Cooperation among wireless devices by exploiting Device-to-Device (D2D) connections is promising, where aggregated resources in a cooperative setup can be utilized by all devices, which would increase the total utility of the setup. In this paper, we focus on the resource allocation problem for cooperating IoT devices with multiple heterogeneous applications. In particular, we develop Application-Aware Cooperative Time allocation (AACT) framework, which optimizes the time that each application utilizes the aggregated system resources by taking into account heterogeneous device constraints and application requirements. AACT is grounded on the concept of Rolling Horizon Control (RHC) where decisions are made by iteratively solving a convex optimization problem over a moving control window of estimated system parameters. The simulation results demonstrate significant performance gains