The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.

Edge Computing: Vision and Challenges

Reliability at massive scale is one of the biggest challenges we face at Amazon.com, one of the largest e-commerce operations in the world; even the slightest outage has significant financial consequences and impacts customer trust. The Amazon.com platform, which provides services for many web sites worldwide, is implemented on top of an infrastructure of tens of thousands of servers and network components located in many datacenters around the world. At this scale, small and large components fail continuously and the way persistent state is managed in the face of these failures drives the reliability and scalability of the software systems.This paper presents the design and implementation of Dynamo, a highly available key-value storage system that some of Amazon's core services use to provide an "always-on" experience. To achieve this level of availability, Dynamo sacrifices consistency under certain failure scenarios. It makes extensive use of object versioning and application-assisted conflict resolution in a manner that provides a novel interface for developers to use.

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Dynamo: amazon's highly available key-value store

Cassandra is a distributed storage system for managing very large amounts of structured data spread out across many commodity servers, while providing highly available service with no single point of failure. Cassandra aims to run on top of an infrastructure of hundreds of nodes (possibly spread across different data centers). At this scale, small and large components fail continuously. The way Cassandra manages the persistent state in the face of these failures drives the reliability and scalability of the software systems relying on this service. While in many ways Cassandra resembles a database and shares many design and implementation strategies therewith, Cassandra does not support a full relational data model; instead, it provides clients with a simple data model that supports dynamic control over data layout and format. Cassandra system was designed to run on cheap commodity hardware and handle high write throughput while not sacrificing read efficiency.

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Cassandra: a decentralized structured storage system

Together with an explosive growth of the mobile applications and emerging of cloud computing concept, mobile cloud computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud computing into the mobile environment and overcomes obstacles related to the performance (e.g., battery life, storage, and bandwidth), environment (e.g., heterogeneity, scalability, and availability), and security (e.g., reliability and privacy) discussed in mobile computing. This paper gives a survey of MCC, which helps general readers have an overview of the MCC including the definition, architecture, and applications. The issues, existing solutions, and approaches are presented. In addition, the future research directions of MCC are discussed. Copyright © 2011 John Wiley & Sons, Ltd.

A survey of mobile cloud computing: architecture, applications, and approaches

Mobile applications are becoming increasingly ubiquitous and provide ever richer functionality on mobile devices. At the same time, such devices often enjoy strong connectivity with more powerful machines ranging from laptops and desktops to commercial clouds. This paper presents the design and implementation of CloneCloud, a system that automatically transforms mobile applications to benefit from the cloud. The system is a flexible application partitioner and execution runtime that enables unmodified mobile applications running in an application-level virtual machine to seamlessly off-load part of their execution from mobile devices onto device clones operating in a computational cloud. CloneCloud uses a combination of static analysis and dynamic profiling to partition applications automatically at a fine granularity while optimizing execution time and energy use for a target computation and communication environment. At runtime, the application partitioning is effected by migrating a thread from the mobile device at a chosen point to the clone in the cloud, executing there for the remainder of the partition, and re-integrating the migrated thread back to the mobile device. Our evaluation shows that CloneCloud can adapt application partitioning to different environments, and can help some applications achieve as much as a 20x execution speed-up and a 20-fold decrease of energy spent on the mobile device.

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CloneCloud: elastic execution between mobile device and cloud

Distributed denial-of-service (DDoS) is a rapidly growing problem. The multitude and variety of both the attacks and the defense approaches is overwhelming. This paper presents two taxonomies for classifying attacks and defenses, and thus provides researchers with a better understanding of the problem and the current solution space. The attack classification criteria was selected to highlight commonalities and important features of attack strategies, that define challenges and dictate the design of countermeasures. The defense taxonomy classifies the body of existing DDoS defenses based on their design decisions; it then shows how these decisions dictate the advantages and deficiencies of proposed solutions.

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A taxonomy of DDoS attack and DDoS defense mechanisms

Distributed denial-of-service (DDoS) attacks present an Internet-wide threat. We propose D-WARD, a DDoS defense system deployed at source-end networks that autonomously detects and stops attacks originating from these networks. Attacks are detected by the constant monitoring of two-way traffic flows between the network and the rest of the Internet and periodic comparison with normal flow models. Mismatching flows are rate-limited in proportion to their aggressiveness. D-WARD offers good service to legitimate traffic even during an attack, while effectively reducing DDoS traffic to a negligible level. A prototype of the system has been built in a Linux router. We show its effectiveness in various attack scenarios, discuss motivations for deployment, and describe associated costs.

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Attacking DDoS at the source

We describe a new approach to power saving and battery life extension on an untethered laptop through wireless remote processing of power-costly tasks. We ran a series of experiments comparing the power consumption of processes run locally with that of the same processes run remotely. We examined the trade-off between communication power expenditures and the power cost of local processing. This paper describes our methodology and results of our experiments. We suggest ways to further improve this approach, and outline a software design to support remote process execution.

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Saving portable computer battery power through remote process execution

Forcing all IP packets to carry correct source addresses can greatly help network security, attack tracing, and network problem debugging. However, due to asymmetries in today's Internet routing, routers do not have readily available information to verify the correctness of the source address for each incoming packet. In this paper we describe a new protocol, named SAVE, that can provide routers with the information needed for source address validation. SAVE messages propagate valid source address information from the source location to all destinations, allowing each router along the way to build an incoming table that associates each incoming interface of the router with a set of valid source address blocks. This paper presents the protocol design and evaluates its correctness and performance by simulation experiments. The paper also discusses the issues of protocol security, the effectiveness of partial SAVE deployment, and the handling of unconventional forms of network routing, such as mobile IP and tunneling.

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SAVE: source address validity enforcement protocol

The Transmission Control Protocol (TCP) carries most Internet traffic, so performance of the Internet depends to a great extent on how well TCP works. Performance characteristics of a particular version of TCP are defined by the congestion control algorithm it employs. This paper presents a survey of various congestion control proposals that preserve the original host-to-host idea of TCP-namely, that neither sender nor receiver relies on any explicit notification from the network. The proposed solutions focus on a variety of problems, starting with the basic problem of eliminating the phenomenon of congestion collapse, and also include the problems of effectively using the available network resources in different types of environments (wired, wireless, high-speed, long-delay, etc.). In a shared, highly distributed, and heterogeneous environment such as the Internet, effective network use depends not only on how well a single TCP-based application can utilize the network capacity, but also on how well it cooperates with other applications transmitting data through the same network. Our survey shows that over the last 20 years many host-to-host techniques have been developed that address several problems with different levels of reliability and precision. There have been enhancements allowing senders to detect fast packet losses and route changes. Other techniques have the ability to estimate the loss rate, the bottleneck buffer size, and level of congestion. The survey describes each congestion control alternative, its strengths and its weaknesses. Additionally, techniques that are in common use or available for testing are described.

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Peter Reiher

Papers

A taxonomy of DDoS attack and DDoS defense mechanisms

Attacking DDoS at the source

Saving portable computer battery power through remote process execution

SAVE: source address validity enforcement protocol

Host-to-Host Congestion Control for TCP