Imran Ahmed

SPARCO: Stochastic Performance Analysis with Reliability and Cooperation for Underwater Wireless Sensor Networks

Reliability is a key factor for application-oriented Underwater Sensor Networks (UWSNs) which are utilized for gaining certain objectives and a demand always exists for efficient data routing mechanisms. Cooperative routing is a promising technique which utilizes the broadcast feature of wireless medium and forwards data with cooperation using sensor nodes as relays. Here, we present a cooperation-based routing protocol for underwater networks to enhance their performance called Stochastic Performance Analysis with Reliability and Cooperation (SPARCO). Cooperative communication is explored in order to design an energy-efficient routing scheme for UWSNs. Each node of the network is assumed to be consisting of a single omnidirectional antenna and multiple nodes cooperatively forward their transmissions taking advantage of spatial diversity to reduce energy consumption. Both multihop and single-hop schemes are exploited which contribute to lowering of path-losses present in the channels connecting nodes and forwarding of data. Simulations demonstrate that SPARCO protocol functions better regarding end-to-end delay, network lifetime, and energy consumption comparative to noncooperative routing protocol—improved Adaptive Mobility of Courier nodes in Threshold-optimized Depth-based routing (iAMCTD). The performance is also compared with three cooperation-based routing protocols for UWSN: Cognitive Cooperation (Cog-Coop), Cooperative Depth-Based Routing (CoDBR), and Cooperative Partner Node Selection Criteria for Cooperative Routing (Coop Re and dth).

Cost and Load Reduction Using Heuristic Algorithms in Smart Grid

Due to smart grid applications the consumers and producers are able to meet the demand of each others and thus take part in demand side management and demand response program. Hence smart grid leads to optimization of energy consumption and reduce high cost in today extensive demand of energy. In this research work we are reducing electricity consumption cost and load consumption using scheduling the appliances. The twenty appliances are used to schedule their energy consumption and load using heuristics techniques i.e. binary particle optimization, genetic algorithm and wind driven optimization, using the same data set for each technique and their results are compared with each other in order to find which technique do better optimization. Simulations are performed in matlab to show the cost and load reduction by the above three techniques and validate the experiment. The simulation results show that binary particle swarm optimization perform better than the other two techniques and wind driven optimization is better than genetic algorithm but not able to perform as binary particle swarm optimization, similarly genetic algorithm is least efficient as compared to both methods. Our research work is beneficial to meet the demand side management and help in reducing electricity cost and load for consumers.

An Improved Forwarding of Diverse Events with Mobile Sinks in Underwater Wireless Sensor Networks

In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput.

MRI Imaging, Comparison of MRI with other Modalities, Noise in MRI Images and Machine Learning Techniques for Noise Removal: A Review

BACKGROUND Medical imaging is to assume greater and greater significance in an efficient and precise diagnosis process. DISCUSSION It is a set of various methodologies which are used to capture internal or external images of the human body and organs for clinical and diagnosis needs to examine human form for various kind of ailments. Computationally intelligent machine learning techniques and their application in medical imaging can play a significant role in expediting the diagnosis process and making it more precise. CONCLUSION This review presents an up-to-date coverage about research topics which include recent literature in the areas of MRI imaging, comparison with other modalities, noise in MRI and machine learning techniques to remove the noise.

AnyCasting In Dual Sink Approach (ACIDS) for WBASNs

After successful development in health-care services, WBASN is also being used in other fields where continuous and distant health-care monitoring is required. Various suggested protocols presented in literature work to enhance the performance of WBASN by focusing on delay, energy efficiency and routing. In this research we focus to increase the stability period and throughput, while decreasing end-to-delay. Two sink nodes are utilized and concept of AnyCasting is introduced. In this research, we have presented a scheme AnyCasting In Dual Sink (ACIDS) for WBASN and compared it with existing protocols LAEEBA and DARE. The performance of ACIDS is found to be 51% and 13% efficient than LAEEBA and DARE respectively in throughput. Results show that, the stability period of ACIDS is much greater than LAEEBA and DARE with minimum delay. Energy parameter in ACIDS is in tradeoff with the improved parameters, due to the computation of RSSI which does more processing and utilizes more energy.

MRI Images Enhancement Using Genetic Programming Based Hybrid Noise Removal Filter Approach

Medical Resonance Imaging (MRI) images degradation is still a challenging task. The noise is a compulsory destructive factor that gets added in MRI images due to several environmental and mechanical reasons. In this paper, an effort is made and a Genetic Programming (GP) based hybrid noise removal approach is proposed which reduces the effect of Rician noise of MRI images. The proposed approach preserves the structural and edges details of the regions of the images. The proposed GP approach uses Feature Extraction phase, GP based Optimal Expression module and Optimal Extraction based Estimation module to remove Rician noise. To validate the proposed approach, the proposed method is tested on different medical samples and the obtained results are compared with results retrieved through the existing comparative approaches. The experimental results show that the proposed approach performs efficiently and can be implemented in real world applications.

Wireless-powered cooperative energy aware anycast routing in wireless sensor networks

A wireless-powered cooperative energy aware anycast routing protocol is proposed in this work. In contrary to conventional cooperative networks, it is considered here that all the relays did not have embedded energy supply, rather equipped with rechargeable batteries and energy harvesting units. Hence, from source signals, they accumulate sufficient harvested energy before the information is forwarded to its destination. Each relay between two basic modes will switch adaptively, which are information forwarding and energy harvesting. The research is limited to decode-and-forward scheme and fixed ratio combining, which works at the relay node of the network and the receiver end, respectively. The physical layer cooperative diversity and network layer multi-hop routing lead us to devise a minimum energy routing protocol as the joint optimization of power required for transmission at physical layer and also at network layer for the process to select a link. Simulating our algorithm demonstrates that the suggested cooperative energy aware anycast routing scheme has a better end-to-end delay and better ratio of packet delivery. Results further reveal that our proposed algorithm has improved energy consumption in comparison to the non-cooperative energy aware anycast scheme and the cooperation-based robust cooperative routing protocol scheme. Sensed data are allocated between nearby nodes by cooperative energy aware anycast routing in a cost-effective way in order to achieve maximum network lifetime.

Investigating Impact of ACK in Non-beacon Enabled Slotted IEEE 802.15.4

IEEE 802.15.4 standard is gaining attention of researchers day by day due to its wide application arena. Till now numerous studies have conducted and yet lot more is in progress for understanding and rounding off sharp edges of this standard. This study briefly describes the standard i.e. IEEE 802.15.4 and explicitly non-beacon enabled slotted CSMA/CA. In slotted or non-beacon enabled CSMA/CA there are further two flavors. One deals with transmission of an extra control packet (ACK frame) on successfully reception of data packet however, other flavor do not transmit any control packet representing successful transmission. In later part of this paper, extensive simulations are conducted in comparison with these two flavors. Our studies imply to use non-ACK mode in low scalable environment ensuring high probability of getting channel access, low delay and better good put.