Bioans: bio-inspired ambient intelligence protocol for wireless sensor networks

This paper describes the BioANS (Bio-inspired Autonomic Networked Services) protocol that uses a novel utility-based service selection mechanism to drive autonomicity in sensor networks. Due to the increase in complexity of sensor network applications, self-configuration abilities, in terms of service discovery and automatic negotiation, have become core requirements. Further, as such systems are highly dynamic due to mobility and/or unreliability; runtime self-optimisation and self-healing is required. However the mechanism to implement this must be lightweight due to the sensor nodes being low in resources, and scalable as some applications can require thousands of nodes. BioANS incorporates some characteristics of natural emergent systems and these contribute to its overall stability whilst it remains simple and efficient. We show that not only does the BioANS protocol implement autonomicity in allowing a dynamic network of sensors to continue to function under demanding circumstances, but that the overheads incurred are reasonable. Moreover, state-flapping between requester and provider, message loss and randomness are not only tolerated but utilised to advantage in the new protocol

Trap-Assisted Tunneling in the Schottky Barrier

The paper presents a new way how to calculate the currents in a Schottky barrier. The novel phenomeno-logical model extends the Shockley-Read-Hall recombi-nation-generation theory of trap-assisted tunneling. The proposed approach explains the occurrence of large leakage currents in Schottky structures on wide band semi-conductors with a high Schottky barrier (above 1 eV) and with a high density of traps. Under certain conditions, trap-assisted tunneling (TAT) plays a more important role than direct tunneling

Threat modeling for communication security of IoT-enabled digital logistics

The modernization of logistics through the use of Wireless Sensor Network (WSN) Internet of Things (IoT) devices promises great efficiencies. Sensor devices can provide real-time or near real-time condition monitoring and location tracking of assets during the shipping process, helping to detect delays, prevent loss, and stop fraud. However, the integration of low-cost WSN/IoT systems into a pre-existing industry should first consider security within the context of the application environment. In the case of logistics, the sensors are mobile, unreachable during the deployment, and accessible in potentially uncontrolled environments. The risks to the sensors include physical damage, either malicious/intentional or unintentional due to accident or the environment, or physical attack on a sensor, or remote communication attack. The easiest attack against any sensor is against its communication. The use of IoT sensors for logistics involves the deployment conditions of mobility, inaccesibility, and uncontrolled environments. Any threat analysis needs to take these factors into consideration. This paper presents a threat model focused on an IoT-enabled asset tracking/monitoring system for smart logistics. A review of the current literature shows that no current IoT threat model highlights logistics-specific IoT security threats for the shipping of critical assets. A general tracking/monitoring system architecture is presented that describes the roles of the components. A logistics-specific threat model that considers the operational challenges of sensors used in logistics, both malicious and non-malicious threats, is then given. The threat model categorizes each threat and suggests a potential countermeasure

The limits of LoRaWAN in event-triggered wireless networked control systems

Wireless sensors and actuators offer benefits to large industrial control systems. The absence of wires for communication reduces the deployment cost, maintenance effort, and provides greater flexibility for sensor and actuator location and system architecture. These benefits come at a cost of a high probability of communication delay or message loss due to the unreliability of radio-based communication. This unreliability poses a challenge to contemporary control systems that are designed with the assumption of instantaneous and reliable communication. Wireless sensors and actuators create a paradigm shift in engineering energy-efficient control schemes coupled with robust communication schemes that can maintain system stability in the face of unreliable communication. This paper investigates the feasibility of using the low-power wide-area communication protocol LoRaWAN with an event-triggered control scheme through modelling in Matlab. We show that LoRaWAN is capable of meeting the maximum delay and message loss requirements of an event-triggered controller for certain classes of applications. We also expose the limitation in the use of LoRaWAN when message size or communication range requirements increase or the underlying physical system is exposed to significant external disturbances

Treatment with 5-Fluorouracil and Celecoxib Displays Synergistic Regression of Ultraviolet Light B-Induced Skin Tumors

Standard chemotherapeutic agents used for the treatment of pre-cancerous skin lesions and non-melanoma skin cancers are not completely effective. Several studies have suggested that repeated inflammatory sunburn reactions, which include the induction of cyclooxygenase-2 (COX-2) and the subsequent production of prostaglandins, play a role in skin cancer development. COX-2 inhibition has been demonstrated to be a potent means of preventing skin cancer development in mice; however, COX-2 inhibitors alone are not effective as chemotherapeutic agents. Data in a variety of cancer types suggest greater efficacy in treating tumors with combination chemotherapies. Therefore, we hypothesized that a combination of the chemotherapeutic agent 5-fluorouracil (5-FU) and the COX-2 inhibitor and anti-inflammatory drug celecoxib would act synergistically to regress tumors in a murine model of ultraviolet light B- (UVB-) induced carcinogenesis. We found that topical treatment with 5-FU and celecoxib together was up to 70% more effective in reducing the number of UVB-induced skin tumors than 5-FU treatment alone. Our data suggest that more effective chemotherapy regimens can be developed to treat the millions of pre-cancerous and cancerous skin lesions that arise every year, which could ultimately lead to a significant reduction in costs and cosmetic defects (scarring) associated with surgical interventions

Design and evaluation of jamming resilient cyber-physical systems

There is a growing movement to retrofit ageing, large scale infrastructures, such as water networks, with wireless sensors and actuators. Next generation Cyber-Physical Systems (CPSs) are a tight integration of sensing, control, communication, computation and physical processes. The failure of any one of these components can cause a failure of the entire CPS. This represents a system design challenge to address these interdependencies. Wireless communication is unreliable and prone to cyber-attacks. An attack upon the wireless communication of CPS would prevent the communication of up-to-date information from the physical process to the controller. A controller without up-to-date information is unable to meet system's stability and performance guarantees. We focus on design approach to make CPSs secure and we evaluate their resilience to jamming attacks aimed at disrupting the system's wireless communication. We consider classic time-triggered control scheme and various resource-aware event-triggered control schemes. We evaluate these on a water network test-bed against three jamming strategies: constant, random, and protocol aware. Our test-bed results show that all schemes are very susceptible to constant and random jamming. We find that time-triggered control schemes are just as susceptible to protocol aware jamming, where some event-triggered control schemes are completely resilient to protocol aware jamming. Finally, we further enhance the resilience of an event-triggered control scheme through the addition of a dynamical estimator that estimates lost or corrupted data