Cross Layered Network Condition Aware Mobile-Wireless Multimedia Sensor Network Routing Protocol for Mission Critical Communication

The high pace emergence in wireless technologies have given rise to an immense demand towards Quality of Service (QoS) aware multimedia data transmission over mobile wireless multimedia sensor network (WMSN). Ensuring reliable communication over WMSN while fulfilling timely and optimal packet delivery over WMSN can be of great significance for emerging IoT ecosystem. With these motivations, in this paper a highly robust and efficient cross layered routing protocol named network condition aware mobile-WMSN routing protocol (NCAM-RP) has been developed. NCAM-RP introduces a proactive neighbour table management, congestion awareness, packet velocity estimation, dynamic link quality estimation (DLQE), and deadline sensitive service differentiation based multimedia traffic prioritization, and multi-constraints based best forwarding node selection mechanisms. These optimization measures have been applied on network layer, MAC layer and the physical layer of the protocol stack that eventually strengthen NCAM-RP to enable QoS-aware multimedia data transmission over WMSNs. The proposed NCAM-RP protocol intends to optimize real time mission critical (even driven) multimedia data (RTMD) transmission while ensuring best feasible resource allocation to the non-real time (NRT) data traffic over WMSNs. NCAM-RP has outperform RPAR based routing scheme in terms of higher data delivery, lower packet drops and deadline miss ratio. It signifies that NCAM-RP can ensure minimal retransmission that eventually can reduce energy consumption, delay and computational overheads. Being the mobility based WMSN protocol, NCAM-RP can play significant role in IoT ecosystem

QUANTUM PHASE SHIFT FOR ENERGY CONSERVED SECURED DATA COMMUNICATION IN MANET

A Mobile Ad-Hoc Network(MANET) is a structure-less network where the mobile nodes randomly moved in any direction within the transmission range of the network. Due to this mobility, wide range of intrusion occurs in MANET. Therefore, Intrusion Detection Systems (IDS) are significant in MANETs to identify the malicious behavior. In order to improve the secured data communication an efficient Quantum Phase Shift Energy Conserved Data Security (QPSEC-DS) technique is introduced. The Quantum Phase Shift (QPS) technique is used for ensuring the security during the data transmission from sender to receiver in MANET. Initially, the quantum based approach is used to encrypt the information using QPS at the sender through secret key distribution. The receiver side also performs the same QPS, and then the encrypted bit is received successfully. This in turns attains the secured packet transmission without any malicious node in the MANET. Based on the phase shifting, the energy conservation between the sender and receiver is measured for transmitting the data packet using QPSEC-DS technique. Also, the enhanced Dynamic Source Routing (DSR) protocol is applied in QPSEC-DS technique is implemented to improve the energy management and secured data communication between the source and destination in an efficient manner. The QPSEC-DS technique conducts the simulations work on parameters including packet delivery ratio, energy consumption, communication overhead and end to end delay

Dynamic Network State Learning Model for Mobility Based WMSN Routing Protocol

The rising demand of wireless multimedia sensor networks (WMSNs) has motivated academia-industries to develop energy efficient, Quality of Service (QoS) and delay sensitive communication systems to meet major real-world demands like multimedia broadcast, security and surveillance systems, intelligent transport system, etc. Typically, energy efficiency, QoS and delay sensitive transmission are the inevitable requirements of WMSNs. Majority of the existing approaches either use physical layer or system level schemes that individually can’t assure optimal transmission decision to meet the demand. The cumulative efficiency of physical layer power control, adaptive modulation and coding and system level dynamic power management (DPM) are found significant to achieve these demands. With this motivation, in this paper a unified model is derived using enhanced reinforcement learning and stochastic optimization method. Exploiting physical as well as system level network state information, our proposed dynamic network state learning model (NSLM) applies stochastic optimization to learn network state-activity that derives an optimal DPM policy and PHY switching scheduling. NSLM applies known as well as unknown network state variables to derive transmission and PHY switching policy, where it considers DPM as constrained Markov decision process (MDP) problem. Here,the use of Hidden Markov Model and Lagrangian relaxation has made NSLM convergence swift that assures delay-sensitive, QoS enriched, and bandwidth and energy efficient transmission for WMSN under uncertain network conditions. Our proposed NSLM DPM model has outperformed traditional Q-Learning based DPM in terms of buffer cost, holding cost, overflow, energy consumption and bandwidth utilization