21,152 research outputs found
Energy-Efficient dynamic virtual network traffic engineering for north-south traffic in multi-location data center networks
We consider the problem of allocating data center (DC) resources for cloud enterprise customers who require guaranteed services on demand. In particular, a request from an enterprise customer is mapped to a virtual network (VN) class that is allocated both bandwidth and compute resources by connecting it from an entry point of a data center to one or more hosts while there are multiple geographically distributed data centers to choose from. We take a dynamic traffic engineering approach over multiple time periods in which an energy-aware resource reservation model is solved at each review point. For the energy-aware resource reservation problem, we present a mixed-integer linear programming (MILP) formulation (for small-scale problems) and a heuristic approach (for large-scale problems). Our heuristic is fast for solving large-scale problems where the MILP problem becomes difficult to solve. Through a comprehensive set of studies, we found that a VN class with a low resource requirement has a low blocking even in heavy traffic, while the VN class with a high resource requirement faces a high service denial. Furthermore, the VN class having randomly distributed resource requirement has a high provisioning cost and blocking compared to the VN class having the same resource requirement for each request although the average resource requirement is same for both these VN classes. We also observe that our approach reduces the maximum energy consumption by about one-sixth at the low arrival rate to by about one-third at the highest arrival rate this also depends on how many different CPU frequency levels a server can run at. (C) 2017 Published by Elsevier B.V
Software Defined Networks based Smart Grid Communication: A Comprehensive Survey
The current power grid is no longer a feasible solution due to
ever-increasing user demand of electricity, old infrastructure, and reliability
issues and thus require transformation to a better grid a.k.a., smart grid
(SG). The key features that distinguish SG from the conventional electrical
power grid are its capability to perform two-way communication, demand side
management, and real time pricing. Despite all these advantages that SG will
bring, there are certain issues which are specific to SG communication system.
For instance, network management of current SG systems is complex, time
consuming, and done manually. Moreover, SG communication (SGC) system is built
on different vendor specific devices and protocols. Therefore, the current SG
systems are not protocol independent, thus leading to interoperability issue.
Software defined network (SDN) has been proposed to monitor and manage the
communication networks globally. This article serves as a comprehensive survey
on SDN-based SGC. In this article, we first discuss taxonomy of advantages of
SDNbased SGC.We then discuss SDN-based SGC architectures, along with case
studies. Our article provides an in-depth discussion on routing schemes for
SDN-based SGC. We also provide detailed survey of security and privacy schemes
applied to SDN-based SGC. We furthermore present challenges, open issues, and
future research directions related to SDN-based SGC.Comment: Accepte
Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges
With the rapid development of marine activities, there has been an increasing
number of maritime mobile terminals, as well as a growing demand for high-speed
and ultra-reliable maritime communications to keep them connected.
Traditionally, the maritime Internet of Things (IoT) is enabled by maritime
satellites. However, satellites are seriously restricted by their high latency
and relatively low data rate. As an alternative, shore & island-based base
stations (BSs) can be built to extend the coverage of terrestrial networks
using fourth-generation (4G), fifth-generation (5G), and beyond 5G services.
Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs.
Despite of all these approaches, there are still open issues for an efficient
maritime communication network (MCN). For example, due to the complicated
electromagnetic propagation environment, the limited geometrically available BS
sites, and rigorous service demands from mission-critical applications,
conventional communication and networking theories and methods should be
tailored for maritime scenarios. Towards this end, we provide a survey on the
demand for maritime communications, the state-of-the-art MCNs, and key
technologies for enhancing transmission efficiency, extending network coverage,
and provisioning maritime-specific services. Future challenges in developing an
environment-aware, service-driven, and integrated satellite-air-ground MCN to
be smart enough to utilize external auxiliary information, e.g., sea state and
atmosphere conditions, are also discussed
Cost Optimization and Load Balancing of Intra and Inter Data Center Networks to Facilitate Cloud Services
Title from PDF of title page viewed January 3, 2019Dissertation advisor: Deep MedhiVitaIncludes bibliographical references (pages 127-137}Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2018For cloud enterprise customers that require services on demand, data centers (DC)
must allocate and partition data center resources in a dynamic fashion. We consider the
problem of allocating data center resources for cloud enterprise customers who require
guaranteed services on demand. In particular, a request from an enterprise customer is
mapped to a virtual network (VN) class that is allocated both bandwidth and compute
resources by connecting it from an entry point of a data center to one or more hosts
while there are multiple geographically distributed data centers to choose from. We take
a dynamic traffic engineering approach over multiple time periods in which an energy
aware resource reservation model is solved at each review point. In this dissertation, at
first for the energy-aware resource reservation problem, we present a mixed-integer linear
programming (MILP) formulation (for small-scale problems) and a heuristic approach
(for large-scale problems). Our heuristic is fast for solving large-scale problems where
the MILP problem becomes difficult to solve. Through a comprehensive set of studies,
we found that a VN class with a low resource requirement has a low blocking even in
heavy traffic, while the VN class with a high resource requirement faces a high service
denial. Furthermore, the VN class having randomly distributed resource requirement
has a high provisioning cost and blocking compared to the VN class having the same
resource requirement for each request although the average resource requirement is same
for both these VN classes. We also observe that our approach reduces the maximum
energy consumption by about one-sixth at the low arrival rate to by about one-third at the
highest arrival rate which also depends on how many different CPU frequency levels a
server can run at.
Allocation of resources in data centers needs to be done in a dynamic fashion
for cloud enterprise customers who require virtualized reservation-oriented services on
demand. Due to the spatial diversity of data centers, the cost of using different DCs also
varies. In this dissertation, we then propose an allocation scheme to balance the load
among these DCs with different cost to minimize the total provisioning cost in a dynamic
environment while ensuring that the service level agreements (SLAs) are met. Compared
to a benchmark scheme (where all requests are first sent to the cheapest data center), our
scheme can decrease the proportional utilization from 24% (for heavy load) to 30% (for
normal load) and achieve a significant balance in the cost incurred by individual DCs. Our
scheme can also achieve 7.5% reduction in total provisioning cost under certain service
level agreement (SLA) in exchange of low increment in blocking. Furthermore, we tested
our scheme on 5 DCs to show that our allocation schemes follows the weighted cost
proportionally.
With the increasing dependency of cloud-based services, data centers have be
come a popular platform to satisfy customers’ requests. Many large network providers
now have their own geographically distributed DCs for cloud services, or have partner
ships with third party DC providers to route customers’ demand. When end customers’ re
quests arrive at a Point-of-Presence (PoP) of a large Internet Service Provider, the provider
having DCs in multiple geo-locations needs to decide which DC should serve the request
depending on the geo-distance, cost of resources in that DC, availability of the requested
resource at that DC, and congestion in the path from the customers’ location to that DC.
Therefore, an optimal connectivity scheme from the ingress PoP to egress DC is required
among the PoPs and DCs to minimize the cost of establishing paths between a PoP and a
DC while ensuring load balancing in both the link level and DC level. Considering these,
we also present a novel mix-integer linear programming (MILP) model for this problem.
We show the efficacy of our model through various performance metrics such as average
and maximum link utilization, and average number of links used per path.Introduction -- Literature review -- Model and heuristic for intra DC cost optimization -- Simulation setup and result analysis for intra DC cost optimization -- Load balancing in geo-distributed data centers -- Optimal connectivity between inter DC networks -- Conclusion and future research -- Appendix A. Intra DC optimization model in AMPL -- Appendix B. Optimal connectivity to inter DC network model in AMP
Novel Resource and Energy Management for 5G Integrated Backhaul/Fronthaul (5G-Crosshaul)
The integration of both fronthaul and backhaul into a single transport network (namely, 5G-Crosshaul) is envisioned for the future 5G transport networks. This requires a fully integrated and unified management of the fronthaul and backhaul resources in a cost-efficient, scalable and flexible way through the deployment of an SDN/NFV control framework. This paper presents the designed 5G-Crosshaul architecture, two selected SDN/NFV applications targeting for cost-efficient resource and energy usage: the Resource Management Application (RMA) and the Energy Management and Monitoring Application (EMMA). The former manages 5G-Crosshaul resources (network, computing and storage resources). The latter is a special version of RMA with the focus on the objectives of optimizing the energy consumption and minimizing the energy footprint of the 5G-Crosshaul infrastructure. Besides, EMMA is applied to the mmWave mesh network and the high speed train scenarios. In particular, we present the key application design with their main components and the interactions with each other and with the control plane, and then we present the proposed application optimization algorithms along with initial results. The first results demonstrate that the proposed RMA is able to cost-efficiently utilize the Crosshaul resources of heterogeneous technologies, while EMMA can achieve significant energy savings through energy-efficient routing of traffic flows. For experiments in real system, we also set up Proof of Concepts (PoCs) for both applications in order to perform real trials in the field.© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
On the placement of security-related Virtualised Network Functions over data center networks
Middleboxes are typically hardware-accelerated appliances such as firewalls, proxies, WAN optimizers, and NATs that play an important role in service provisioning over today's data centers. Reports show that the number of middleboxes is on par with the number of routers, and consequently represent a significant commitment from an operator's capital and operational expenditure budgets. Over the past few years, software middleboxes known as Virtual Network Functions (VNFs) are replacing the hardware appliances to reduce cost, improve the flexibility of deployment, and allow for extending network functionality in short timescales.
This dissertation aims at identifying the unique characteristics of security modules implementation as VNFs in virtualised environments. We focus on the placement of the security VNFs to minimise resource usage without violating the security imposed constraints as a challenge faced by operators today who want to increase the usable capacity of their infrastructures. The work presented here, focuses on the multi-tenant environment where customised security services are provided to tenants. The services are implemented as a software module deployed as a VNF collocated with network switches to reduce overhead. Furthermore, the thesis presents a formalisation for the resource-aware placement of security VNFs and provides a constraint programming solution along with examining heuristic, meta-heuristic and near-optimal/subset-sum solutions to solve larger size problems in reduced time.
The results of this work identify the unique and vital constraints of the placement of security functions. They demonstrate that the granularity of the traffic required by the security functions imposes traffic constraints that increase the resource overhead of the deployment. The work identifies the north-south traffic in data centers as the traffic designed for processing for security functions rather than east-west traffic. It asserts that the non-sharing strategy of security modules will reduce the complexity in case of the multi-tenant environment. Furthermore, the work adopts on-path deployment of security VNF traffic strategy, which is shown to reduce resources overhead compared to previous approaches
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