CAFE (collaborative agents for filtering e-mails) is a multi-agent system to collaboratively filter spam and classify legitimate messages in users' mail stream. CAFE associates a proxy agent with each user, and this agent represents a sort of interface between the user's e-mail client and the e-mail server. With the support of other types of agents, the proxy agent makes a classification of new messages into three categories: ham (good messages), spam and spam-presumed. Ham messages can be in their turn divided on the basis of the sender's identity and reputation. The reputation is collaboratively inferred from users' ratings. The filtering process is performed using three kinds of approach: a first approach based on the usage of an hash function, a static approach using DNSBL (DNS-based black lists) databases and a dynamic approach based on a Bayesian filter. We give a mathematical representation of the system, showing that if users collaborate, the fault probability decreases in proportion to the number of active users.

Today's crowdsourcing systems are predominantly used for processing independent tasks with simplistic coordination. As such, they offer limited support for handling complex, intellectually and organizationally challenging labour types, such as software development. In order to support crowdsourcing of the software development processes, the system needs to enact coordination mechanisms which integrate human creativity with machine support. While workflows can be used to handle highly-structured and predictable labour processes, they are less suitable for software development methodologies where unpredictability is an unavoidable part the process. This is especially true in phases of requirement elicitation and feature development, when both the client and development communities change with time. In this paper we present models and techniques for coordination of human workers in crowdsourced software development environments. The techniques augment the existing Social Compute Unit (SCU) concept---a general framework for management of ad-hoc human worker teams---with versatile coordination protocols expressed in the Lightweight Social Calculus (LSC). This approach allows us to combine coordination and quality constraints with dynamic assessments of software-user's desires, while dynamically choosing appropriate software development coordination models.

Crowdsourcing is generally used for tasks with minimal coordination, providing limited support for dynamic reconfiguration. Modern systems, exemplified by social ma chines, are subject to continual flux in both the client and development communities and their needs. To support crowdsourcing of open-ended development, systems must dynamically integrate human creativity with machine support. While workflows can be u sed to handle structured, predictable processes, they are less suitable for social machine development and its attendant uncertainty. We present models and techniques for coordination of human workers in crowdsourced software development environments. We combine the Social Compute Unit—a model of ad-hoc human worker teams—with versatile coordination protocols expressed in the Lightweight Social Calculus. This allows us to combine coordination and quality constraints with dynamic assessments of end-user desires, dynamically discovering and applying development protocols.

Software Defined Networks (SDN), the separation of a network device’s control and data planes, do not need to rely on the underlying network equipment (routers, switches, firewall).It is a new network which collaborated IP and a lot of relevant technical content. The control of SDN is completely open, the user can customize any rule strategy to achieve network routing and transmission, which is more flexible and intelligent. Internet Protocol version 6 (IPv6), with the 128-bit address, is the next generation Internet. In this paper, we present a Flow Table structure by using Flow Label and a matching approach which use Flow Label within IPv6 protocol to decrease the size of Flow Table with OpenFlow and the time of forwarding IPv6 packets in SDN based on OpenFlow. The simulations and analyses show that this flow table mechanism performs better.

Ultra Wideband (UWB) is an promising underlying method for coexistence among different systems. However, the performance may not be as good as expected due to the changing spectrum environment. Thus, cognitive UWB radio is proposed by taking the advantage of cognition, which enables the radio to learn the spectrum environment by itself. In this paper, we explore a cognitive UWB testbed in physical layer, including cognitive pulse generator, stream view and performance evaluation. In order to protect the potential narrowband systems, the specific mask and channel information are utilized to adapt the system parameters with the help of pulse mask code and pulse generation block. Simulation results show that the proposed testbed is capable to generate the adaptive pulse that suitable for different spectrum environment.

This paper analyzes the performance of a proposed subcarriers sharing scheme. According to the scheme, secondary system helps the primary system via two phase Decode and Forward orthogonal frequency division multiplexing based relaying. If primary (licensed user) is unable to achieve its target rate then secondary transmitter (which is located within a critical distance from primary transmitter) will provide few subcarriers to primary receiver, to fulfill the requirement of the primary system and remaining subcarriers can be used by secondary (cognitive) system for its own data transmission. If secondary transmitter is located at or beyond the critical distance from primary transmitter then no spectrum sharing is possible. The analytic expression of outage probability of the primary and secondary system has been computed. Through theoretical and simulation results it has been shown that the primary outage probability with cooperation (while secondary transmitter acts a partial relay) is less than the outage probability for direct transmission. Therefore opportunistic spectrum sharing can be achieved by secondary system.

Owing to retransmission of lost packets and bursty nature of source data, even an ad hoc network with low average traffic may suffer heavy traffic in some certain periods, which in further may degrade system performance, particularly in multi-hop wireless communication. Aiming to provide a solution to above problem, in this paper, we construct a hybrid system based on plural ad hoc networks, which are defined as primary radio networks (PRNs), and a secondary radio network (SRN). In the hybrid system, a cooperative relay scheme based on dynamic spectrum access, defined as cognitive relay, is adopted for retransmitting the lost packets of PRNs. Cognitive relay is carried out by SRN in spectrum hole. Simulation-based evaluation shows that the proposed cognitive relay, compared to existing retransmission protocol, is more effective in providing QoS-guaranteed communication.

The Robotic Ecology vision shares many similarities with the one pursued by the IoT community: The ideal aim on both fronts is that arbitrary combinations of devices should be able to be deployed in unstructured environments, such as those exemplified in a typical household, and there efficiently cooperate to the achievement of complex tasks. While this has the potential to deliver a range of modular and disruptive applications, a pressing and open research question is how to reduce the amount of pre-programming required for their deployment in real world applications. In order to inspire similar advancements within the IoT community, this extended abstract discusses how this goal has been addressed by pioneering the concept of a self-learning robotic ecology within the EU project RUBICON (Robotic UBIquitous Cognitive Network); how such an approach relates to the concept of Affordances at the basis of Gibsons’ theory of ecological psychology; and how it can be used to drive the gradual adaptation of a robotic ecology to changing contexts and evolving requirements.

In this paper, we propose to mitigate the effect of inter-symbol interference (ISI) by first interleaving symbols labelled by bits in one codeword with symbols respectively labelled by bits in the two adjacent codewords and then transmitting the interleaved symbol vectors through the ISI channel. At the receiver, we not only perform turbo equalization between the equalizer and the channel decoder, but also exchange extrinsic information between adjacent codewords since the interleaved structure of the proposed scheme. If the adjacent codewords are decoded reliably, we can cancel the interference from adjacent codewords and hence the performance can be improved. Simulation results show that the proposed scheme can achieve better error performance as compared to the conventional scheme based on either the same code length or the same decoding latency.

As wireless sensor networks mature, it becomes clear that the raw data collected by this technology can only be used in a meaningful way if it can be analyzed automatically. Describing the behavior of the data with a model, and then looking at the parameters of the model, or detecting differences between the model and the real data, is how experimental data is typically used in other fields. The work presented here aims at facilitating the use of sensor data models to describe the expected behavior of the sensor observations. The processing of such models can be pushed into the wireless sensor network to eliminate redundant information as early in the data collection chain as possible, thus minimizing both bandwidth requirements and energy consumption.