A survey of performance enhancement of transmission control protocol (TCP) in wireless ad hoc networks

Mast, Noor; Owens, Tom

doi:10.1186/1687-1499-2011-96

Cited by 18 publications

(10 citation statements)

References 54 publications

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“…So the proposed FBCGC algorithm utilizes Fibonacci sequence based Cwnd growth rate to limit the number of data segments to be transferred. FBCGC starts with 1 MSS and impose Fibonacci increment on Cwnd ie Cwnd size= (1,2,3,5,8,13,24, …) till it reaches slow start threshold. After receiving ACK for the first data segment, 2 segments are transmitted.…”

Section: B Fibonacci Based Congestion Control Alorithmmentioning

confidence: 99%

“…To be more specific, TCP usually overloads the network by injecting more packets without knowing contention and congestion level [3]. Specifically, when TCP is implemented over IEEE 802.11 MAC in multihop network, TCP wrongly perceives contention losses at MAC layer as packet loss due to high congestion level and slows down the transmission rate rapidly to resolve the congestion.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Cross Layer Approach to Enhance QoS Performance in Multihop Adhoc Networks

Nithya

Mala

Sivasankar

2014

2014 17th International Conference on Network-Based Information Systems

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To enhance the QoS performance in saturated multihop adhoc networks, it is essential to have cooperative algorithms for MAC layer contention resolution and TCP layer congestion control. This paper proposes a cross layer approach that modifies the backoff mechanism and congestion control technique using Fibonacci sequence. Due to the golden section property of Fibonacci sequence, contention and congestion can be effectively controlled. The NS2 simulation results show that the proposed algorithm drastically enhances the QoS performance of 802.11 multihop adhoc networks.

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Section: B Fibonacci Based Congestion Control Alorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Cross Layer Approach to Enhance QoS Performance in Multihop Adhoc Networks

Nithya

Mala

Sivasankar

2014

2014 17th International Conference on Network-Based Information Systems

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“…Several efforts have been made to optimize the performance of TCP over MANET [4]. We focus on research work based on lower layer feedbacks.…”

Section: Literature Reviewmentioning

confidence: 99%

CTCP : A Cross-Layer Information Based TCP for MANET

Bhatia¹,

Kumar²

2014

IJASUC

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Traditional TCP cannot detect link contention losses and route failure losses which occur in MANET and considers every packet loss as congestion. This results in severe degradation of TCP performance. In this research work, we modified the operations of TCP to adapt to network states. The cross-layer notifications are used for adapting the congestion window and achieving better performance. We propose Cross-layer information based Transmission Control Protocol (CTCP) which consists of four network states. Decelerate state to recover from contention losses, Cautionary state to deal with route failures, Congested state to handle network congestion and Normal state to be compatible with traditional TCP. Decelerate state makes TCP slow down if the packet loss is believed to be due to contention rather than congestion. Cautionary state suspends the TCP variables and after route reestablishment resumes with conservative values. Congestion state calls congestion control when network is actually congested and normal state works as standard TCP. Simulation results show that network state based CTCP is more appropriate for MANET than packet loss based traditional TCP.

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“…Much of the existing study on IoT has focused on addressing the power and computational resource constraints by the design of specific routing, MAC, and cross-layer protocols [14,15]. However, for specific applications, further efforts should be directed toward finding ways to improve the sensing efficiency and minimize the data transmitted between sensor nodes.…”

Section: Related Studymentioning

confidence: 99%

Design and implementation of a distributed fall detection system based on wireless sensor networks

Luo

Liu

et al. 2012

J Wireless Com Network

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Pervasive healthcare is one of the most important applications of the Internet of Things (IoT). As part of the IoT, the wireless sensor networks (WSNs) are responsible for sensing the abnormal behavior of the elderly or patients. In this article, we design and implement a fall detection system called SensFall. With the resource restricted sensor nodes, it is vital to find an efficient feature to describe the scene. Based on the optical flow analysis, it can be observed that the thermal energy variation of each sub-region of the monitored region is a salient spatio-temporal feature that characterizes the fall. The main contribution of this study is to develop a feature-specific sensing system to capture this feature so as to detect the occurrence of a fall. In our system, the three-dimensional (3D) object space is segmented into some distinct discrete sampling cells, and pyroelectric infrared (PIR) sensors are employed to detect the variance of the thermal flux within these cells. The hierarchical classifier (two-layer HMMs) is proposed to model the time-varying PIR signal and classify different human activities. We use self-developed PIR sensor nodes mounted on the ceiling and construct a WSN based on ZigBee (802.15.4) protocol. We conduct experiments in a real office environment. The volunteers simulate several kinds of activities including falling, sitting down, standing up from a chair, walking, and jogging. Encouraging experimental results confirm the efficacy of our system.

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A survey of performance enhancement of transmission control protocol (TCP) in wireless ad hoc networks

Cited by 18 publications

References 54 publications

A Novel Cross Layer Approach to Enhance QoS Performance in Multihop Adhoc Networks

A Novel Cross Layer Approach to Enhance QoS Performance in Multihop Adhoc Networks

CTCP : A Cross-Layer Information Based TCP for MANET

Design and implementation of a distributed fall detection system based on wireless sensor networks

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