We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

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

Part I: AN INTRODUCTION TO INQUIRY. 1. Human Inquiry and Science. 2. Paradigms, Theory, and Research. 3. The Ethics and Politics of Social Research. Part II: THE STRUCTURING OF INQUIRY: QUANTITATIVE AND QUALITATIVE. 4. Research Design. 5. Conceptualization, Operationalization, and Measurement. 6. Indexes, Scales, and Typologies. 7. The Logic of Sampling. Part III: MODES OF OBSERVATION: QUANTITATIVE AND QUALITATIVE. 8. Experiments. 9. Survey Research. 10. Qualitative Field Research. 11. Unobtrusive Research. 12. Evaluation Research. Part IV: ANALYSIS OF DATA:QUANTITATIVE AND QUALITATIVE . 13. Qualitative Data Analysis. 14. Quantitative Data Analysis. 15. Reading and Writing Social Research. Appendix A. Using the Library. Appendix B. Random Numbers. Appendix C. Distribution of Chi Square. Appendix D. Normal Curve Areas. Appendix E. Estimated Sampling Error.

社会研究方法基础 = The Basics of Social Research

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.

Technological evolution of mobile user equipment (UEs), such as smartphones or laptops, goes hand-in-hand with evolution of new mobile applications. However, running computationally demanding applications at the UEs is constrained by limited battery capacity and energy consumption of the UEs. A suitable solution extending the battery life-time of the UEs is to offload the applications demanding huge processing to a conventional centralized cloud. Nevertheless, this option introduces significant execution delay consisting of delivery of the offloaded applications to the cloud and back plus time of the computation at the cloud. Such a delay is inconvenient and makes the offloading unsuitable for real-time applications. To cope with the delay problem, a new emerging concept, known as mobile edge computing (MEC), has been introduced. The MEC brings computation and storage resources to the edge of mobile network enabling it to run the highly demanding applications at the UE while meeting strict delay requirements. The MEC computing resources can be exploited also by operators and third parties for specific purposes. In this paper, we first describe major use cases and reference scenarios where the MEC is applicable. After that we survey existing concepts integrating MEC functionalities to the mobile networks and discuss current advancement in standardization of the MEC. The core of this survey is, then, focused on user-oriented use case in the MEC, i.e., computation offloading. In this regard, we divide the research on computation offloading to three key areas: 1) decision on computation offloading; 2) allocation of computing resource within the MEC; and 3) mobility management. Finally, we highlight lessons learned in area of the MEC and we discuss open research challenges yet to be addressed in order to fully enjoy potentials offered by the MEC.

Mobile Edge Computing: A Survey on Architecture and Computation Offloading

Existing signaling solutions are insufficient in terms of inter-domain and out-of-path signaling, mobility support and inter-working with policy and security mechanisms. The paper presents the Cross-Application Signaling Protocol (CASP) which is a general-purpose protocol for managing state information in network devices. This technology independent signaling protocol can be used for inter- and intra-domain QoS signaling, the configuration of middleboxes, for collecting measurement data and any other application where state management is required. It relies on existing transport protocols and consists of a messaging layer and a client layer. The messaging layer is application independent and is responsible for routing, session establishment and feature negotiation. In contrast to this application independent component of CASP, the client layer is the application-dependent part. As an example for a client the paper describes the QoS Resource Allocation Client for CASP and discusses requirements for extending CASP to include interdomain signaling.. The discovery of next peers along the data path is handled by the Scout protocol, which is a specialized client protocol. Some of the basic mechanisms are derived from existing protocols. This way the design of this protocol relies on the experiences made in this area and is therefore one of the promising protocol candidates for the IETF NSIS WG.

Design of CASP - a Technology Independent Lightweight Signaling Protocol

The ping-pong type of movement is a typical motion manner in mobile IPv6 networks, which will bring frequent handovers and thus increase signaling burden. On the other hand, reducing handover delay in this case seems to be more significant. In this paper, we propose a fast seamless handover scheme for the ping-pong type of movement as an extension to the hierarchical mobile IPv6. Based on the simulation results, it can be observed that, by setting the reservation active flag (RAF) and the offline count down timer (CDT), the scheme significantly reduces QoS signaling cost and handover delay. Furthermore, the simulations work out an optimized CDT for acquiring better cost performance of resource reservation

Fast seamless handover scheme and cost performance optimization for ping-pong type of movement

As networks grow in scale and complexity, the use of Network Function Virtualization (NFV) and the ability to dynamically instantiate network function instances (NFls) allow us to scale out the network's capabilities in response to demand. At the same time, an increasing number of computing resources, deployed closer to users, as well as network equipment are now capable of performing general-purpose computation for NFV. However, NFV management in the presence of Service Function Chaining (SFC) for arbitrary topologies is a challenging task. In this work we argue for the necessity of an algorithmic resource managementframework that captures the involved tradeoffs of NFls minimum workload, load balancing, and flow path stretch. We introduce DRENCH as a low complexity NFV and flow steering management framework. In DRENCH an NFV market is considered where a centralised SDN controller acts as market orchestrator of NFV nodes. Through competition, NFV nodes make flow steering and NFl instantiation/consolidation decisions. DRENCH design enables third party NFV nodes participation while it can coexist with other NFV management solutions. DRENCH orchestrator parameterisation strikes the right balance between path stretch and NFl load balancing, resulting in significantly lower Flow Completion Times, up to 1Ox less, in some cases.

/pdf/drench-a-semi-distributed-resource-management-framework-for-4qybmb21tw.pdf

DRENCH: A semi-distributed resource management framework for NFV based service function chaining

RSVP version 1 has been designed for optimum support multicast. However, in reality multicast is being used much less frequently than anticipated. Still, even for unicast (one sender, one receiver) full-fledged multicast-enabled RSVP signaling must be used. As pointed out in the NSIS requirement draft, multicast would not be necessarily required for an NSIS signaling protocol. This draft analyses ingredients of RSVP Version 1 which are affected by multicast, and derives how these ingredients may look like if multicast is not supported in the generic RSVP signaling protocol and adapt related functionalities accordingly we call the resulting feature set ”RSVP Lite”, a potentially more light-weight version of RSVP. This report is equivalent to the Internet draft “Analysis on RSVP Regarding Multicast” (draft-fu-rsvp-multicast-analysis-01.txt), October 2002. Network Working Group X. Fu Internet-Draft University of Goettingen Expires: April 16, 2003 C. Kappler H. Tschofenig Siemens AG October 16, 2002 Analysis on RSVP Regarding Multicast draft-fu-rsvp-multicast-analysis-01.txt Status of this Memo This document is an Internet-Draft and is in full conformance with all provisions of Section 10 of RFC2026. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as InternetDrafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." The list of current Internet-Drafts can be accessed at http:// www.ietf.org/ietf/1id-abstracts.txt. The list of Internet-Draft Shadow Directories can be accessed at http://www.ietf.org/shadow.html. This Internet-Draft will expire on April 16, 2003.

Analysis on RSVP Regarding Multicast

AS-level end-to-end paths are of great value for ISPs and a variety of network applications. Although tools like traceroute may reveal AS paths, they require the permission to access source hosts and introduce additional probing traffic, which is not feasible in many applications. In contrast, AS path inference based on BGP control plane data and AS relationship information is a more practical and cost-effective approach. However, this approach suffers from a limited accuracy and high traffic, especially when AS paths are long. In this paper, we bring a new angle to the AS path inference problem by exploiting the metrical tree-likeness or low hyperbolicity of the Internet, part of the complex network properties of the Internet. We show that such property can generate a new constraint that narrows down the searching space of possible AS paths to a much smaller size. Based on this observation, we propose two new AS path inference algorithms, namely HyperPath and Valley-free HyperPath. With intensive evaluations on AS paths from real-world BGP Routing Information Bases, we show that the proposed new algorithms can achieve superior performance, in particular, when AS paths are long paths. We demonstrate that our algorithms can significantly reduce inter-AS traffic for P2P applications with an improved AS path prediction accuracy.

Xiaoming Fu

Papers

Design of CASP - a Technology Independent Lightweight Signaling Protocol

Fast seamless handover scheme and cost performance optimization for ping-pong type of movement

DRENCH: A semi-distributed resource management framework for NFV based service function chaining

Analysis on RSVP Regarding Multicast

AS path inference: From complex network perspective