A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing

The emergence of cloud computing based on virtualization technologies brings huge opportunities to host virtual resource at low cost without the need of owning any infrastructure. Virtualization technologies enable users to acquire, configure and be charged on pay-per-use basis. However, Cloud data centers mostly comprise heterogeneous commodity servers hosting multiple virtual machines (VMs) with potential various specifications and fluctuating resource usages, which may cause imbalanced resource utilization within servers that may lead to performance degradation and service level agreements (SLAs) violations. To achieve efficient scheduling, these challenges should be addressed and solved by using load balancing strategies, which have been proved to be NP-hard problem. From multiple perspectives, this work identifies the challenges and analyzes existing algorithms for allocating VMs to PMs in infrastructure Clouds, especially focuses on load balancing. A detailed classification targeting load balancing algorithms for VM placement in cloud data centers is investigated and the surveyed algorithms are classified according to the classification. The goal of this paper is to provide a comprehensive and comparative understanding of existing literature and aid researchers by providing an insight for potential future enhancements.Comment: 22 Pages, 4 Figures, 4 Tables, in pres

Network Aware VM Migration using Community Recognition

Cloud Computing is a powerful concept buzzing these days in industry by which we can avail resources as and when we require like electricity and where required softwares and information are provided based on demand. It enables us with large computing power with low-cost and hence removes the hassle of storing and maintaining servers locally. It can be basically divided into three of business i.e. Software as a Service, Platform as a Service and Infrastructure as a Service which helps to transfer service to end user very efficiently. VM placement belongs to the model of the Infrastructure as a Service. Basically it means that all applications have a certain need of computing power, memory storage, network bandwidth, and some power consumption to function which is abstracted as a Virtual Machine and provided by the Data Centers. Virtual Machine Migration is the method of transferring the VMs to the Physical Machines in such a way that there is efficient usage of energy, network bandwidth, etc. I have proposed a new network aware VM Migration scheme using Community Recognition which shows the candidates for migration and takes into account all other factors like energy, migration criteria, etc

An Experimental Study on Virtual Machine Live Migration Impact on Services Performance

One important benefit of servers' virtualization is the reduction of the maintenance complexity of infrastructures. A key feature is servers' live migration which allows virtual servers to be exchanged between physical machines without stopping their services. However, virtualization also has some drawbacks caused by the overhead generated. Our research evaluated live migration process overhead, on real and virtual environments, noticed from the client's side regarding two different services: web and database. YCSB and ab Benchmark were adopted as workloads. Almost all tests on real environment overcame those on virtual, with both benchmarks. The impact of the live migration in the services was evident, proving to be more effective on real machines than on virtual machines. We found the DB service accommodated better to the virtual environment and to migration than Web service. We also considered an environment with multiple migrations which presented a higher degradation than when only one migration is performed

Exploring the firewall security consistency in cloud computing during live migration

Virtualization technology adds great opportunities and challenges to the cloud computing paradigm. Resource management can be efficiently enhanced by employing Live Virtual Machine Migration (LVMM) techniques. Based on the literature of LVMM implementation in the virtualization environment, middle-boxes such as firewalls do not work effectively after LVMM as it introduces dynamic changes in network status and traffic, which may lead to critical security vulnerabilities. One key security hole is that the security context of the firewall do not move with the Virtual Machine after LVMM is triggered. This leads to inconsistency in the firewall level of protection of the migrated Virtual Machine. There is a lack in the literature of practical studies that address this problem in cloud computing platform. This paper demonstrates a practical analysis using OpenStack testbed to study the firewalls limitations in protecting virtual machines after LVMM. Two network scenarios are used to evaluate this problem. The results show that the security context problem does not exist in the stateless firewall but can exist in the stateful firewall

Mitigating Interference During Virtual Machine Live Migration through Storage Offloading

Today\u27s cloud landscape has evolved computing infrastructure into a dynamic, high utilization, service-oriented paradigm. This shift has enabled the commoditization of large-scale storage and distributed computation, allowing engineers to tackle previously untenable problems without large upfront investment. A key enabler of flexibility in the cloud is the ability to transfer running virtual machines across subnets or even datacenters using live migration. However, live migration can be a costly process, one that has the potential to interfere with other applications not involved with the migration. This work investigates storage interference through experimentation with real-world systems and well-established benchmarks. In order to address migration interference in general, a buffering technique is presented that offloads the migration\u27s read, eliminating interference in the majority of scenarios

Memory Management and Reuse Mechanism for Virtual Machine in Cloud Computing to Minimize Energy Consumption : A Review Paper

Cloud computing is an emerging computing technology for large data centers that maintains computational resources through the internet, rather than on local computers. VM migration provides the capability to balance the load, system maintenance and fault tolerance, etc. However, existing migration techniques, used to migrate virtual machines keeping memory images of VMs in host and skipping transfer of unchanged memory pages to reduce the amount of transfer data during migration, if number of migrations increases, number of memory images stored on host are also increased, this causes memory starvation.  In this paper, a propose technique that reduces the size of memory image stored on source host before migration.  When a VM migrates to other host, memory images of VM is kept in the source host after removing unwanted data according to the Probability factor. When the VM migrates back to the original host later, the kept memory image will be “reused”, i.e. data which are identical to the kept data will not be transferred and comparative to existing system the size of memory image is small. To validate this approach, evaluate the results using different threshold levels and probability factor of change in data. Proposed system required less memory to store the memory image and allow more VMs to be hosted. Specifically, proposed work is used to improve resource efficiency throughout by reducing the size of memory image that is stored on source host. Keywords: Cloud computing, Migration, Virtualization, Virtual Machine, Physical Machine, Live Virtual Machine Migration