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

D-MORE: Dynamic mesh-based overlay peer-to-peer infrastructure

Soft state provides new services to packet-switching networks by introducing a type of state in the network nodes which is refreshed by periodical messages and otherwise expires. The operations of soft state protocols, which are being designed with ever greater complexity, need to be error-free and deadlock-free to avoid misusing network resources. Thus, verification, formal analysis and validation of these protocols become a vital task. In this paper we utilize formal techniques, specifically, Specification and Description Language (SDL) and Message Sequence Charts (MSCs), for modeling, analysis and validation of various soft state protocols. We propose a general architecture for state management systems and find employing these techniques can help identify and correct possible design errors, which may be caused by informal specifications.

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Modeling soft state protocols with SDL

A vast majority of spam emails today are sent from botnets with forged sender addresses. This has attracted researchers over the years to develop email sender authentication mechanism as a promising way to verify identity of the senders. In this paper we introduce iSATS, a new email sender authentication system based on Identity-based public key cryptography. iSATS leverages an identity based signature scheme to provide a reliable and easy way to bind the identity of legitimate sender to an email. Unlike the popular existing solutions like SPF and DKIM, it is hard for the spammer to adopt iSATS.

iSATS: Leveraging Identity based Sender Authentication for Spam Mitigation

Real-time interactive multimedia applications are highly delay-sensitive, and packets that are out of delay boundaries are usually obsolete. However the current Internet Protocol lacks a way to control the lifetime of the packets explicitly. We propose a packet lifetime control mechanism called Explicit Delay Control (EDC) that embeds a Maximum Tolerable Delay (MTD) field in an IPv4 option. At each network node, the MTD is deducted by the singlehop delay. Packets that expire their lifetime are discarded and non-congestion related delay losses are signaled to the sender to reduce inaccuracy in delay estimations and to adapt to path changes. We implemented EDC in the Linux kernel. Our evaluation has shown that EDC is an effective scheme to ensure the “legality” of the packets, reduce the waste of bandwidth and processing time in the networks, and alleviate congestions.

Principles and experiments of explicit delay control

Mobility support was one of the shortcommings of RSVP and a number of proposals have been made in the past to improve various features. This document attempts to determine what the expected functionality is, how various problems can be solved and what implications are caused by certain design decisions.

Xiaoming Fu

Papers

D-MORE: Dynamic mesh-based overlay peer-to-peer infrastructure

Modeling soft state protocols with SDL

iSATS: Leveraging Identity based Sender Authentication for Spam Mitigation

Principles and experiments of explicit delay control

Mobility Support in NSIS