Convergence of Distributed Clouds Grids and their Management

Here is an excerpt from the WETICE2013 Track #3 -Convergence of Distributed Clouds, Grids and Their Management

 

Virtualization, Cloud Computing and the Emerging Datacenter Complexity Cliff

Convergence of Distributed Clouds, Grids and their Management – CDCGM2013

WETICE2013 – Hammamet, June 17 – 20, 2013

Track Chair’s Report

Dr. Rao Mikkilineni, IEEE Member, and Dr. Giovanni Morana

Abstract

The Convergence of distributed clouds, grids and their management conference track focuses on virtualization and cloud computing as they enjoy wider acceptance. A recent IDC report predicts that by 2016, $1 of every $5 will be spent on cloud-based software and infrastructure. Three papers address key issues in cloud computing such as resource optimization and scaling to address changing workloads and energy management.  In addition, the DIME network architecture proposed in WETICE2010 is discussed in two papers in this conference, both showing its usefulness in addressing fault, configuration, accounting, performance and security of service transactions with in the service oriented architecture implementation and also spanning across multiple clouds.

While virtualization has brought resource elasticity and application agility to the services infrastructure management, the resulting layers of orchestration and the lack of end-to-end service visibility and control spanning across multiple service provider infrastructure have added an alarming degree of complexity. Hopefully, reducing the complexity in the next generation datacenters will be a major research topic in this conference.

Introduction

While virtualization and cloud computing have brought elasticity to computing resources and agility to applications in a distributed environment, they have also increased complexity of managing various distributed applications contributing to a distributed service transaction delivery by adding layers of orchestration and management systems. There are three major factors contributing to the complexity:

  1. Current IT datacenters have evolved from their server-centric, low-bandwidth origins to distributed and high-bandwidth environments where resources can be dynamically allocated to applications using computing, network and storage resource virtualization. While Virtual machines improve resiliency and provide live migration to reduce the recovery time objectives in case of service failures, the increased complexity of hypervisors, their orchestration, Virtual Machine images and their movement and management adds an additional burden in the datacenter. A recent global survey commissioned by Symantec Corporation involving 2,453 IT professionals at organizations in 32 countries concludes [1] that the complexity introduced by virtualization, cloud computing and proliferation of mobile devices is a major problem. The survey asked respondents to rate the level of complexity in each of five areas on a scale of 0 to 10, and the results show that data center complexity affects all aspects of computing, including security and infrastructure, disaster recovery, storage and compliance. For example, respondents on average rated all the areas 6.56 or higher on the complexity scale, with security topping the list at 7.06. The average level of complexity for all areas for companies around the world was 6.69. The survey shows that organizations in the Americas on average rated complexity highest, at 7.81, and those in Asia-Pacific/Japan lowest, at 6.15.
  2. As the complexity increases, the response is to introduce more automation of resource administration and operational controls. However, the increased complexity of management of services may be more a fundamental architectural issue related to Gödel’s prohibition of self-reflection in Turing machines [2] than a software design or an operational execution issue. Cockshott et al. [3] conclude their book “Computation and its limits” with the paragraph “The key property of general-purpose computer is that they are general purpose. We can use them to deterministically model any physical system, of which they are not themselves a part, to an arbitrary degree of accuracy. Their logical limits arise when we try to get them to model a part of the world that includes themselves.” Automation of dynamic resource administration at run-time makes the computer itself a part of the model and also a part of the problem.
  3. As the services increasingly span across multiple datacenters often owned and operated by different service providers and operators, it is unrealistic to expect that more software that coordinates the myriad resource management systems belonging to different owners is the answer for reducing complexity. A new approach that decouples the service management from underlying distributed resource management systems which are often non-communicative and cumbersome is in order.

The current course becomes even more untenable with the advent of many-core severs with tens and even hundreds of computing cores with high bandwidth communication among them. It is hard to imagine replicating current TCP/IP based socket communication, “isolate and fix” diagnostic procedures, and the multiple operating systems (which do not have end-to-end visibility or control of business transactions that span across multiple cores, multiple chips, multiple servers and multiple geographies) inside the next generation many-core servers without addressing their shortcomings.  The many-core servers and processors constitute a network where each node itself is a sub-network with different bandwidths and protocols (socket-based low bandwidth communication between servers, InfiniBand, or PCI Express bus based communication across processors in the same server and shared memory based low latency communication across the cores inside the processor).

The tradition that started in WETICE2009 “to analyze current trends in Cloud Computing and identify long-term research themes and facilitate collaboration in future research in the field that will ultimately enable global advancements in the field that are not dictated or driven by the prototypical short term profit driven motives of a particular corporate entity” has resulted in a new computing model that was included in the Turing Centenary Conference proceedings in 2012 [3, 4]. Two papers in this conference continue the investigation of its usefulness. Hopefully, this tradition will result in other novel and different approaches to address the datacenter complexity issue while incremental improvements continue as is evident from another three papers.

http://wetice.org

 

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