Wireless Sensor Networks (WSNs) are composed of tiny sensor nodes able to monitor environmental conditions. Existing applications for WSNs usually adopt a centralized approach that exploit sensor nodes just for sensing, while data processing takes place on more powerful base stations. This can be considered a consequence of the common WSN programming practice that proves too rigid to support de...

In sensor networks, collaborative processing between multiple sensor nodes is essential in order to complement for each other’s sensing capability, tolerate faults, and provide reliable information. The client/server-based paradigm is typical for distributed processing. However, it is not the most efficient in the context of sensor networks. In this paper, we present a mobileagent-based paradig...

Active-network technology envisions deploying execution environments in network elements so that application-specific processing can be applied to network traffic. To provide safety and efficiency, individual nodes must include mechanisms to manage resource use. This implies nodes must understand resource demands associated with specific traffic. Wellaccepted metrics exist for expressing bandwi...

Distributed graph processing systems increasingly require many compute nodes to cope with the requirements imposed by contemporary graph-based Big Data applications. However, increasing the number of compute nodes increases the chance of node failures. Therefore, provisioning an efficient failure recovery strategy is critical for distributed graph processing systems. This paper proposes a novel...

A wireless sensor network (WSN) is a specialized wireless network that composes of a number of sensor nodes deployed in a specified area for monitoring environment conditions such as temperature, air pressure, humidity, light, motion or vibration, and so on. The sensor nodes are usually programmed to monitor or collect data from surrounding environment and pass the information to the base stati...

Active Network technology envisions deployment of virtual execution environments within network elements, such as switches and routers, so that nonhomogeneous processing can be applied to network traffic associated with services, flows, or even individual packets. To use such a technology safely and efficiently, individual nodes must provide mechanisms to enforce resource limits associated with...

Abstract The rapidly growing computational demands of deep neural networks require novel hardware designs. Recently, tuneable nanoelectronic devices were developed based on hopping electrons through a network dopant atoms in silicon. These ‘dopant processing units’ (DNPUs) are highly energy-efficient and have potentially very high throughput. By adapting the control voltages applied to its elec...

background & objectives: colon cancer is currently of high incidence and mortality rate. identifying the factors influencing its prognosis can be very beneficial to its clinical treatment. recent studies have shown that lymph nodes ratio can be considered as an important prognostic factor. the aim of the present study is to investigate the effect of this factor on the prognosis of the patie...

Adaptive networks include a set of nodes with adaptation and learning abilities for modeling various types of self-organized and complex activities encountered in the real world. This paper presents the effect of heterogeneously distributed incremental least mean-square (LMS) algorithm with ideal links on the quality of unknown parameter estimation. In heterogeneous adaptive networks, a fractio...