1,792 research outputs found
A Survey of Controller Placement Problem in Software Defined Networks
Software Defined Network (SDN) is an emerging network paradigm which provides
a centralized view of the network by decoupling the network control plane from
the data plane. This strategy of maintaining a global view of the network
optimizes resource management. However, the implementation of SDN using a
single physical controller lead to issues of scalability and robustness. A
physically distributed but logically centralized SDN controller architecture
promises to resolve both these issues. Distributed SDN along with its benefits
brings along the problem of the number of controllers required and their
placement in the network. This problem is referred to as the controller
placement problem (CPP) and this paper is mainly concerned with the CPP
solution techniques. The paper formally defines CPP, gives a comprehensive
review of the various performance metrics and characteristics of the available
CPP solutions. Finally, we point out the existing literature gap and discuss
the future research direction in this domain
Management and Orchestration of Network Slices in 5G, Fog, Edge and Clouds
Network slicing allows network operators to build multiple isolated virtual
networks on a shared physical network to accommodate a wide variety of services
and applications. With network slicing, service providers can provide a
cost-efficient solution towards meeting diverse performance requirements of
deployed applications and services. Despite slicing benefits, End-to-End
orchestration and management of network slices is a challenging and complicated
task. In this chapter, we intend to survey all the relevant aspects of network
slicing, with the focus on networking technologies such as Software-defined
networking (SDN) and Network Function Virtualization (NFV) in 5G, Fog/Edge and
Cloud Computing platforms. To build the required background, this chapter
begins with a brief overview of 5G, Fog/Edge and Cloud computing, and their
interplay. Then we cover the 5G vision for network slicing and extend it to the
Fog and Cloud computing through surveying the state-of-the-art slicing
approaches in these platforms. We conclude the chapter by discussing future
directions, analyzing gaps and trends towards the network slicing realization.Comment: 31 pages, 4 figures, Fog and Edge Computing: Principles and
Paradigms, Wiley Press, New York, USA, 201
SDN Partitioning: A Centralized Control Plane for Distributed Routing Protocols
Hybrid IP networks that use both control paradigms - distributed and
centralized - promise the best of two worlds: programmability and agility of
SDN, and reliability and fault tolerance of distributed routing protocols like
OSPF. The common approaches follow a division of labor concept, where SDN
controls prioritized traffic and OSPF assures care-free operation of best
effort traffic. We propose SDN Partitioning, which establishes centralized
control over the distributed routing protocol by partitioning the topology into
sub-domains with SDN-enabled border nodes, such that OSPF's routing updates
have to traverse SDN border nodes to reach neighboring sub-domains. This allows
the central controller to modify how sub-domains view one another, which in
turn allows to steer inter-sub-domain traffic. The degree of dynamic control
against simplicity of OSPF can be trade off by adjusting the size of the
sub-domains. This paper explains the technical requirements, presents a novel
scheme for balanced topology partitioning, and provides the models for common
network management tasks. Our performance evaluation shows that - already in
its minimum configuration with two sub-domains - SDN Partitioning provides
significant improvements in all respects compared to legacy routing protocols,
whereas smaller sub-domains provide network control capabilities comparable to
full SDN deployment.Comment: 14 pages, 12 figure
Virtual Machine Migration Planning in Software-Defined Networks
In this paper, we examine the problem of how to schedule the migrations and
how to allocate network resources for migration when multiple VMs need to be
migrated at the same time. We consider the problem in the Software-defined
Network (SDN) context since it provides flexible control on routing. More
specifically, we propose a method that computes the optimal migration sequence
and network bandwidth used for each migration. We formulate this problem as a
mixed integer programming, which is NP-hard. To make it computationally
feasible for large scale data centers, we propose an approximation scheme via
linear approximation plus fully polynomial time approximation, and obtain its
theoretical performance bound. Through extensive simulations, we demonstrate
that our fully polynomial time approximation (FPTA) algorithm has a good
performance compared with the optimal solution and two state of-the-art
algorithms. That is, our proposed FPTA algorithm approaches to the optimal
solution with less than 10% variation and much less computation time.
Meanwhile, it reduces the total migration time and the service downtime by up
to 40% and 20% compared with the state-of-the-art algorithms, respectively.Comment: To appear at Infocom 201
Can SDN Mitigate Disasters?
Datacenter networks and services are at risk in the face of disasters.
Existing fault-tolerant storage services cannot even achieve a nil recovery
point objective (RPO) as client-generated data may get lost before the
termination of their migration across geo-replicated datacenters. SDN has
proved instrumental in exploiting application-level information to optimise the
routing of information. In this paper, we propose Software Defined Edge (SDE)
or the implementation of SDN at the network edge to achieve nil RPO. We
illustrate our proposal with a fault-tolerant key-value store that
experimentally recovers from disaster within 30s. Although SDE is inherently
fault-tolerant and scalable, its deployment raises new challenges on the
partnership between ISPs and CDN providers. We conclude that failure detection
information at the SDN-level can effectively benefit applications to recover
from disaster
Survey on Network Virtualization Hypervisors for Software Defined Networking
Software defined networking (SDN) has emerged as a promising paradigm for
making the control of communication networks flexible. SDN separates the data
packet forwarding plane, i.e., the data plane, from the control plane and
employs a central controller. Network virtualization allows the flexible
sharing of physical networking resources by multiple users (tenants). Each
tenant runs its own applications over its virtual network, i.e., its slice of
the actual physical network. The virtualization of SDN networks promises to
allow networks to leverage the combined benefits of SDN networking and network
virtualization and has therefore attracted significant research attention in
recent years. A critical component for virtualizing SDN networks is an SDN
hypervisor that abstracts the underlying physical SDN network into multiple
logically isolated virtual SDN networks (vSDNs), each with its own controller.
We comprehensively survey hypervisors for SDN networks in this article. We
categorize the SDN hypervisors according to their architecture into centralized
and distributed hypervisors. We furthermore sub-classify the hypervisors
according to their execution platform into hypervisors running exclusively on
general-purpose compute platforms, or on a combination of general-purpose
compute platforms with general- or special-purpose network elements. We
exhaustively compare the network attribute abstraction and isolation features
of the existing SDN hypervisors. As part of the future research agenda, we
outline the development of a performance evaluation framework for SDN
hypervisors.Comment: IEEE Communications Surveys and Tutorials, in print, 201
HyMER: A Hybrid Machine Learning Framework for Energy Efficient Routing in SDN
Software-defined networks (SDN) with programmable data plane and machine
learning for discovering patterns are utilized in security, traffic
classification, quality of services prediction, and network performance, that
has increasing research attention. Addressing the significance of energy
efficiency in networks, we propose a novel hybrid machine learning-based
framework named HyMER that combines the capabilities of SDN and machine
learning for traffic-aware energy efficient routing. To the best of our
knowledge, HyMER is the first that utilizes a hybrid machine learning solution
with supervised and reinforcement learning components for energy efficiency and
network performance in SDN. The supervised learning component consists of
feature extraction, training, and testing. The reinforcement learning component
learns from existing data or from scratch by iteratively interacting with the
network environment. The HyMER framework is developed on POX controller and is
evaluated on Mininet using real-world topologies and dynamic traffic traces.
Experimental results show that the supervised component achieves up to 70%
feature size reduction and more than 80\% accuracy in parameter prediction. We
demonstrate that combining the supervised and reinforcement methods not only
does capture the dynamic change more efficiently but also increases the
convergence speed. As compared to state-of-the-art utility based energy saving
approaches, HyMER heuristics has shown up to 50% link saving, and also exhibits
up to 14.7 watts less power consumption for realistic network topology and
traffic traces.Comment: Double column 12 pages, 13 figures, 6 table
DDoS Attacks: Tools, Mitigation Approaches, and Probable Impact on Private Cloud Environment
The future of the Internet is predicted to be on the cloud, resulting in more
complex and more intensive computing, but possibly also a more insecure digital
world. The presence of a large amount of resources organized densely is a key
factor in attracting DDoS attacks. Such attacks are arguably more dangerous in
private individual clouds with limited resources. This paper discusses several
prominent approaches introduced to counter DDoS attacks in private clouds. We
also discuss issues and challenges to mitigate DDoS attacks in private clouds
A Comprehensive Study on Load Balancers for VNF chains Horizontal Scaling
We present an architectural design and a reference implementation for
horizontal scaling of virtual network function chains. Our solution does not
require any changes to network functions and is able to handle stateful network
functions for which states may depend on both directions of the traffic. We use
connection-aware traffic load balancers based on hashing function to maintain
mappings between connections and the dynamically changing network function
chains. Our references implementation uses OpenFlow switches to route traffic
to the assigned network function instances according to the load balancer
decisions. We conducted extensive simulations to test the feasibility of the
architecture and evaluate the performance of our implementation.Comment: Short version of the paper has been accepted for CNSM 201
A Survey on Software-Defined VANETs: Benefits, Challenges, and Future Directions
The evolving of Fifth Generation (5G) networks isbecoming more readily
available as a major driver of the growthof new applications and business
models. Vehicular Ad hocNetworks (VANETs) and Software Defined Networking
(SDN)represent the key enablers of 5G technology with the developmentof next
generation intelligent vehicular networks and applica-tions. In recent years,
researchers have focused on the integrationof SDN and VANET, and look at
different topics related to thearchitecture, the benefits of software-defined
VANET servicesand the new functionalities to adapt them. However, securityand
robustness of the complete architecture is still questionableand have been
largely negleted. Moreover, the deployment andintegration of novel entities and
several architectural componentsdrive new security threats and
vulnerabilities.In this paper, first we survey the state-of-the-art SDN
basedVehicular ad-hoc Network (SDVN) architectures for their net-working
infrastructure design, functionalities, benefits, and chal-lenges. Then we
discuss these SDVN architectures against majorsecurity threats that violate the
key security services such asavailability, confidentiality, authentication, and
data integrity.We also propose different countermeasures to these
threats.Finally, we discuss the lessons learned with the directions offuture
research work towards provisioning stringent security andprivacy solutions in
future SDVN architectures. To the best of ourknowledge, this is the first
comprehensive work that presents sucha survey and analysis on SDVNs in the era
of future generationnetworks (e.g., 5G, and Information centric networking)
andapplications (e.g., intelligent transportation system, and IoT-enabled
advertising in VANETs).Comment: 17 pages, 2 figure
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