Abstract
Advanced driving assistance systems (ADAS) pose stringent requirements to a system’s control and communications, in terms of timeliness and reliability, hence, wireless communications have not been seriously considered a potential candidate for such deployments. However, recent developments in these technologies are supporting unprecedented levels of reliability and predictability. This can enable a new generation of ADAS systems with increased flexibility and the possibility of retrofitting older vehicles. However, to effectively test and validate these systems, there is a need for tools that can support the simulation of these complex communication infrastructures from the control and the networking perspective. This paper introduces a co-simulation framework that enables the simulation of an ADAS application scenario in these two fronts, analyzing the relationship between different vehicle dynamics and the delay required for the system to operate safely, exploring the performance limits of different wireless network configurations. © 2020, Springer Nature Switzerland AG.

Abstract
In a platoon-based vehicular cyber-physical system (PVCPS), a lead vehicle that is responsible for managing the platoon's moving directions and velocity periodically disseminates control messages to the vehicles that follow. Securing wireless transmissions of the messages between the vehicles is critical for privacy and confidentiality of the platoon's driving pattern. However, due to the broadcast nature of radio channels, the transmissions are vulnerable to eavesdropping. In this article, we propose a cooperative secret key agreement (CoopKey) scheme for encrypting/decrypting the control messages, where the vehicles in PVCPS generate a unified secret key based on the quantized fading channel randomness. Channel quantization intervals are optimized by dynamic programming to minimize the mismatch of keys. A platooning testbed is built with autonomous robotic vehicles, where a TelosB wireless node is used for onboard data processing and multi-hop dissemination. Extensive real-world experiments demonstrate that CoopKey achieves significantly low secret bit mismatch rate in a variety of settings. Moreover, the standard NIST test suite is employed to verify randomness of the generated keys, where the p-values of our CoopKey pass all the randomness tests. We also evaluate CoopKey with an extended platoon size via simulations to investigate the effect of system scalability on performance.

Abstract
Deterministic Synchronous Multichannel Extension (DSME) is a prominent MAC behavior first introduced in IEEE 802.15.4e. It can avail deterministic and best effort Service using its multisuperframe structure. RPL is a routing protocol for wireless networks with low power consumption and generally susceptible to packet loss. These two standards were designed independently but with the common objective to satisfy the requirements of IoT devices in terms of limited energy, reliability and determinism. A combination of these two protocols can integrate real-time QoS demanding and large-scale IoT networks. In this paper, we propose a new multi-channel, multi-timeslot scheduling algorithm called Symphony that provides QoS efficient schedules in DSME networks. In this paper we provide analytical and simulation based delay analysis for our approach against some state of the art algorithms. In this work, we show that integrating routing with DSME can improve reliability by 40% and by using Symphony, we can reduce the network delay by 10--20% against the state of the art algorithms.

Abstract
Deterministic Synchronous Multichannel Extension (DSME) is a prominent MAC behavior first introduced in IEEE 802.15.4e supporting deterministic guarantees using its multisuperframe structure. DSME also facilitates techniques like multi-channel and Contention Access Period (CAP) reduction to increase the number of available guaranteed timeslots in a network. However, any tuning of these functionalities in dynamic scenarios is not explored in the standard. In this paper, we present a multisuperframe tuning technique called DynaMO which tunes the CAP reduction and Multisuperframe Order in an effective manner to improve flexibility and scalability, while guaranteeing bounded delay. We also provide simulations to prove that DynaMO with its dynamic tuning feature can offer up to 15--30% reduction in terms of latency in a large DSME network.

Abstract
Over the years, workers have joined in producer organizations to face the difficulties that the capitalist market poses to them. Together they can gain efficiency and equity compared to big companies, and they can gain bargaining power over the product market. In our case, we target smallholder farmers who face many difficulties in increasing their welfare. To overcome them, they group together in producer organizations such as cooperatives. With the development of technology, it became possible for these cooperatives of workers to use the Web to operate - such type of organization and operation is called a Platform Cooperative (PC). This paper presents a multi-agent based modeling of Farmers' Coalition Formation (FCF) for smallholder farmers so that they can operate by means of a Platform cooperative. We present the design of a characteristic function that calculates the coalition values in this context, finds the best way of partitioning the farmers into smaller groups and divides the payoff in a stable manner. We empirically analyze the model using value distributions. The results show that forming coalitions is profitable for farmers. We also proved that the model ensures a fair distribution of the payoff among the farmers.

Abstract
There are many information retrieval tasks over the Web, which cannot be attended with a simple keyword-based lookup search. Such an important exploratory search problem is the comparison of two Web resources. To manually compare two data resources by looking for information from one Web page to another without any software support is inefficient and time-consuming. This paper discusses a solution to automatize the comparison of two data resources present in a RDF graph. In our work, we provide an improvement over the current state-of-the-art method, by reverse engineering SPARQL queries using a hashing based recursive procedure. We empirically verify how hashing could largely benefit in reducing the size of the returned query and hence making it practically comprehensible for users or agents to understand the similarity concepts returned.