192,607 research outputs found
Delay-oriented active queue management in TCP/IP networks
PhDInternet-based applications and services are pervading everyday life. Moreover, the growing
popularity of real-time, time-critical and mission-critical applications set new challenges to
the Internet community. The requirement for reducing response time, and therefore latency
control is increasingly emphasized.
This thesis seeks to reduce queueing delay through active queue management. While
mathematical studies and research simulations reveal that complex trade-off relationships
exist among performance indices such as throughput, packet loss ratio and delay, etc., this
thesis intends to find an improved active queue management algorithm which emphasizes
delay control without trading much on other performance indices such as throughput and
packet loss ratio.
The thesis observes that in TCP/IP network, packet loss ratio is a major reflection of
congestion severity or load. With a properly functioning active queue management algorithm,
traffic load will in general push the feedback system to an equilibrium point in terms of
packet loss ratio and throughput. On the other hand, queue length is a determinant factor on
system delay performance while has only a slight influence on the equilibrium. This
observation suggests the possibility of reducing delay while maintaining throughput and
packet loss ratio relatively unchanged.
The thesis also observes that queue length fluctuation is a reflection of both load changes and
natural fluctuation in arriving bit rate. Monitoring queue length fluctuation alone cannot
distinguish the difference and identify congestion status; and yet identifying this difference is
crucial in finding out situations where average queue size and hence queueing delay can be
properly controlled and reasonably reduced. However, many existing active queue
management algorithms only monitor queue length, and their control policies are solely
based on this measurement. In our studies, our novel finding is that the arriving bit rate
distribution of all sources contains information which can be a better indication of
congestion status and has a correlation with traffic burstiness. And this thesis develops a
simple and scalable way to measure its two most important characteristics, namely the mean
ii
and the variance of the arriving rate distribution. The measuring mechanism is based on a
Zombie List mechanism originally proposed and deployed in Stabilized RED to estimate the
number of flows and identify misbehaving flows. This thesis modifies the original zombie
list measuring mechanism, makes it capable of measuring additional variables. Based on
these additional measurements, this thesis proposes a novel modification to the RED
algorithm. It utilizes a robust adaptive mechanism to ensure that the system reaches proper
equilibrium operating points in terms of packet loss ratio and queueing delay under various
loads. Furthermore, it identifies different congestion status where traffic is less bursty and
adapts RED parameters in order to reduce average queue size and hence queueing delay
accordingly.
Using ns-2 simulation platform, this thesis runs simulations of a single bottleneck link
scenario which represents an important and popular application scenario such as home
access network or SoHo. Simulation results indicate that there are complex trade-off
relationships among throughput, packet loss ratio and delay; and in these relationships delay
can be substantially reduced whereas trade-offs on throughput and packet loss ratio are
negligible. Simulation results show that our proposed active queue management algorithm
can identify circumstances where traffic is less bursty and actively reduce queueing delay
with hardly noticeable sacrifice on throughput and packet loss ratio performances.
In conclusion, our novel approach enables the application of adaptive techniques to more
RED parameters including those affecting queue occupancy and hence queueing delay. The
new modification to RED algorithm is a scalable approach and does not introduce additional
protocol overhead. In general it brings the benefit of substantially reduced delay at the cost
of limited processing overhead and negligible degradation in throughput and packet loss
ratio. However, our new algorithm is only tested on responsive flows and a single bottleneck
scenario. Its effectiveness on a combination of responsive and non-responsive flows as well
as in more complicated network topology scenarios is left for future work
Adaptive management of an active services network
The benefits of active services and networks cannot be realised unless the associated increase in system complexity can be efficiently managed. An adaptive management solution is required. Simulation results show that a distributed genetic algorithm, inspired by observations of bacterial communities, can offer many key management functions. The algorithm is fast and efficient, even when the demand for network services is rapidly varying
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Energy-efficient wireless communication
In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters
Semantic-based policy engineering for autonomic systems
This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise
Integrated Support for Handoff Management and Context-Awareness in Heterogeneous Wireless Networks
The overwhelming success of mobile devices and wireless
communications is stressing the need for the development of
mobility-aware services. Device mobility requires services
adapting their behavior to sudden context changes and being
aware of handoffs, which introduce unpredictable delays and
intermittent discontinuities. Heterogeneity of wireless
technologies (Wi-Fi, Bluetooth, 3G) complicates the situation,
since a different treatment of context-awareness and handoffs is
required for each solution. This paper presents a middleware
architecture designed to ease mobility-aware service
development. The architecture hides technology-specific
mechanisms and offers a set of facilities for context awareness
and handoff management. The architecture prototype works with
Bluetooth and Wi-Fi, which today represent two of the most
widespread wireless technologies. In addition, the paper discusses
motivations and design details in the challenging context of
mobile multimedia streaming applications
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