60,302 research outputs found
Load Balancing and Virtual Machine Allocation in Cloud-based Data Centers
As cloud services see an exponential increase in consumers, the demand for faster processing of data and a reliable delivery of services becomes a pressing concern. This puts a lot of pressure on the cloud-based data centers, where the consumers’ data is stored, processed and serviced. The rising demand for high quality services and the constrained environment, make load balancing within the cloud data centers a vital concern. This project aims to achieve load balancing within the data centers by means of implementing a Virtual Machine allocation policy, based on consensus algorithm technique. The cloud-based data center system, consisting of Virtual Machines has been simulated on CloudSim – a Java based cloud simulator
Effectiveness of segment routing technology in reducing the bandwidth and cloud resources provisioning times in network function virtualization architectures
Network Function Virtualization is a new technology allowing for a elastic cloud and bandwidth resource allocation. The technology requires an orchestrator whose role is the service and resource orchestration. It receives service requests, each one characterized by a Service Function Chain, which is a set of service functions to be executed according to a given order. It implements an algorithm for deciding where both to allocate the cloud and bandwidth resources and to route the SFCs. In a traditional orchestration algorithm, the orchestrator has a detailed knowledge of the cloud and network infrastructures and that can lead to high computational complexity of the SFC Routing and Cloud and Bandwidth resource Allocation (SRCBA) algorithm. In this paper, we propose and evaluate the effectiveness of a scalable orchestration architecture inherited by the one proposed within the European Telecommunications Standards Institute (ETSI) and based on the functional separation of an NFV orchestrator in Resource Orchestrator (RO) and Network Service Orchestrator (NSO). Each cloud domain is equipped with an RO whose task is to provide a simple and abstract representation of the cloud infrastructure. These representations are notified of the NSO that can apply a simplified and less complex SRCBA algorithm. In addition, we show how the segment routing technology can help to simplify the SFC routing by means of an effective addressing of the service functions. The scalable orchestration solution has been investigated and compared to the one of a traditional orchestrator in some network scenarios and varying the number of cloud domains. We have verified that the execution time of the SRCBA algorithm can be drastically reduced without degrading the performance in terms of cloud and bandwidth resource costs
Communication-efficient Distributed Multi-resource Allocation
In several smart city applications, multiple resources must be allocated
among competing agents that are coupled through such shared resources and are
constrained --- either through limitations of communication infrastructure or
privacy considerations. We propose a distributed algorithm to solve such
distributed multi-resource allocation problems with no direct inter-agent
communication. We do so by extending a recently introduced additive-increase
multiplicative-decrease (AIMD) algorithm, which only uses very little
communication between the system and agents. Namely, a control unit broadcasts
a one-bit signal to agents whenever one of the allocated resources exceeds
capacity. Agents then respond to this signal in a probabilistic manner. In the
proposed algorithm, each agent makes decision of its resource demand locally
and an agent is unaware of the resource allocation of other agents. In
empirical results, we observe that the average allocations converge over time
to optimal allocations.Comment: To appear in IEEE International Smart Cities Conference (ISC2 2018),
Kansas City, USA, September, 2018. arXiv admin note: substantial text overlap
with arXiv:1711.0197
Multi-Path Alpha-Fair Resource Allocation at Scale in Distributed Software Defined Networks
The performance of computer networks relies on how bandwidth is shared among
different flows. Fair resource allocation is a challenging problem particularly
when the flows evolve over time. To address this issue, bandwidth sharing
techniques that quickly react to the traffic fluctuations are of interest,
especially in large scale settings with hundreds of nodes and thousands of
flows. In this context, we propose a distributed algorithm based on the
Alternating Direction Method of Multipliers (ADMM) that tackles the multi-path
fair resource allocation problem in a distributed SDN control architecture. Our
ADMM-based algorithm continuously generates a sequence of resource allocation
solutions converging to the fair allocation while always remaining feasible, a
property that standard primal-dual decomposition methods often lack. Thanks to
the distribution of all computer intensive operations, we demonstrate that we
can handle large instances at scale
Performance Analysis of Network-Assisted Two-Hop D2D Communications
Network-assisted single-hop device-to-device (D2D) communication can increase
the spectral and energy efficiency of cellular networks by taking advantage of
the proximity, reuse, and hop gains when radio resources are properly managed
between the cellular and D2D layers. In this paper we argue that D2D technology
can be used to further increase the spectral and energy efficiency if the key
D2D radio resource management algorithms are suitably extended to support
network assisted multi-hop D2D communications. Specifically, we propose a
novel, distributed utility maximizing D2D power control (PC) scheme that is
able to balance spectral and energy efficiency while taking into account mode
selection and resource allocation constraints that are important in the
integrated cellular-D2D environment. Our analysis and numerical results
indicate that multi-hop D2D communications combined with the proposed PC scheme
can be useful not only for harvesting the potential gains previously identified
in the literature, but also for extending the coverage of cellular networks.Comment: 6 pages and 7 figure
Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function Chaining
Service Function Chaining (SFC) allows the forwarding of a traffic flow along
a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT).
Software Defined Networking (SDN) solutions can be used to support SFC reducing
the management complexity and the operational costs. One of the most critical
issues for the service and network providers is the reduction of energy
consumption, which should be achieved without impact to the quality of
services. In this paper, we propose a novel resource (re)allocation
architecture which enables energy-aware SFC for SDN-based networks. To this
end, we model the problems of VNF placement, allocation of VNFs to flows, and
flow routing as optimization problems. Thereafter, heuristic algorithms are
proposed for the different optimization problems, in order find near-optimal
solutions in acceptable times. The performance of the proposed algorithms are
numerically evaluated over a real-world topology and various network traffic
patterns. The results confirm that the proposed heuristic algorithms provide
near optimal solutions while their execution time is applicable for real-life
networks.Comment: Extended version of submitted paper - v7 - July 201
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