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Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

A Survey on Mobile Edge Computing: The Communication Perspective

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.

In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

PORs: Proofs of Retrievability for Large Files

コンピュータ・サイエンス : ACM computing surveys

To guarantee proportional fairness (PF) is an important way to realize predictable and controllable service differentiation. In this paper, a proportional differentiation call admission control (CAC) algorithm, named PBS-PF, is proposed to guarantee the network services' PF in terms of call blocking probability (CBP). PBS-PF is based on the partial bandwidth sharing CAC scheme due to this scheme's high bandwidth utilization rate. PBS-PF dynamically calculates the bandwidth admission threshold of each service class to control the blocking call number for guaranteeing the CBP ratio of high and low priority services to accord with a given value. The simulations show that the CBP of each service class changes with the network load, but their ratio approximately keeps unchanged, which proves the effectiveness of PBS-PF. At last, we analyze the time complexity of PBS-PF.

Proportional fairness of call blocking probability

Pattern-matching is often used in network security mechanisms, which detect the predefined signature strings or keywords starting at an arbitrary location in the payload. Such mechanisms require the network to inspect the packet payload at line rates to filter the worms or virus. These signature sets are large and some signature can be as long as more than 2000 byte. This paper propose a high performance and scalable packet pattern-matching architecture. Bloom filter engines are used in front-end for membership query which can achieve high performance, and an lookup table is used in back-end to performance deterministic string-matching. In order to solve the scalability problem in using Bloom filter to detect long pattern, prefix register heap is used to keep the intermediate status. The architecture can achieve gigabytes throughput with large pattern set and long patterns. A great saving in hardware resource also proves that the architecture is very scalable.

A High Performance and Scalable Packet Pattern-Matching Architecture

This paper proposes an efficient, Adaptive Range-Based Mobile Multicast (ARBMoM) protocol. ARBMoM uses the Multicast Home Agent (MHA) to deliver multicast packets to mobile users. The MHA of a user in ARBMoM is decided not only by its location, but also by its mobility and service characteristics. This makes each router act as either a regular foreign agent (FA) or an MHA, thus balancing the load. To find an optimal service range for an MHA to trade off between the multicast packet delivery and the multicast service disruption latency, we model the user's movement in 2-D mesh network using Markov chain. To reduce the computational complexity, we aggregate the states by using the mobile movement symmetry. In addition, we propose a method to easily obtain the aggregate state set and the transition probability between any two aggregate states once the service range is given. In addition, ARBMoM is compatible with any multicast tree configuration algorithm. Both simulation and numerical results demonstrate that ARBMoM enhances the system performance.

Adaptive range-based mobile multicast

NFV ecosystem is flourishing and more and more NF platforms appear, but this makes NF vendors difficult to deliver NFs rapidly to diverse platforms. We propose an NF development framework named NFD for cross-platform NF development. NFD's main idea is to decouple the functional logic from the platform logic —it provides a platform-independent language to program NFs' behavior models, and a compiler with interfaces to develop platform-specific plugins. By enabling a plugin on the compiler, various NF models would be compiled to executables integrated with the target platform. We prototype NFD, build 14 NFs, and support 6 platforms (standard Linux, OpenNetVM, GPU, SGX, DPDK, OpenNF). Our evaluation shows that NFD can save development workload for cross-platform NFs and output valid and performant NFs.

NFD: Using Behavior Models to Develop Cross-Platform Network Functions

Overlay multicast is now widely used to provide high quality audio and video service, which requires more on its performance. We proposed an application layer multicast mechanism, which is called MO-video (multicast overlay video), based on combination of central-control and distributed self-organization. This mechanism that is highly organized is stable and suitable for live media streaming service. In MO-video network, the media stream is pushed to all users instead of request for data. On the other hand, the network is organized by different areas, which is managed by one control node to minimize the message cast and schedule for the data transmission. The cooperation of control nodes, and the synchronous data sending by the senders, provide a better performance to all users and effectively avoid data redundancy. At the end of the paper, simulations and experiments is delicately designed to show the advantage of MO-video and convince us that it will be a promising mechanism in overly multicast.

Yong Cui

Papers

Proportional fairness of call blocking probability

A High Performance and Scalable Packet Pattern-Matching Architecture

Adaptive range-based mobile multicast

NFD: Using Behavior Models to Develop Cross-Platform Network Functions

MO-Video: An application layer infrastructure for live media streaming