Media features and communication control in the digitalized workplace: a study about regulating negative emotional communication

PurposeOne challenge facing the digitalized workplace is communication control, especially emotion regulation in which individuals try to manage their emotional experiences and/or expressions during organizational communication. Extant research largely focused on the facilitating role of a few media features (e.g. fewer symbol sets). This study seeks to provide a deeper understanding of media features that individuals, as receivers of negative emotions expressed by communication partners, could leverage to support regulating negative emotional communication in the workplace.Design/methodology/approachThis study used qualitative research methods to identify media features that support regulating negative emotional communication at work. Data were collected using interviews and was analyzed using directed content analysis in which media features discussed in media synchronicity theory (MST) were used as the initial coding schema but the researcher was open to media features that do not fit with MST.FindingsIn addition to media features (and capabilities) discussed in MST, this study identified five additional media features (i.e. message broadcasting, message blocking, receiving specification, recipient specification and compartmentalization) and two underlying media capabilities (i.e. transmission control capability and participant control capability) that may support regulating negative emotional communication. Two major mechanisms (i.e. reducing or eliminating emotion regulation workload, and providing prerequisites or removing obstacles for emotion regulation) via which media features support emotion regulation were also identified.Originality/valueThis paper provides a more comprehensive understanding regarding communication media features that may support emotion regulation in particular and communication control in general. Findings of this study contribute to several literatures and may also transfer to other similar contexts.

Machine Learning for Disseminating Cooperative Awareness Messages in Cellular V2V Communications

<div>This paper develops a novel Machine Learning (ML)-based strategy to distribute aperiodic Cooperative Awareness Messages (CAMs) through cellular Vehicle-to-Vehicle (V2V) communications. According to it, an ML algorithm is employed by each vehicle to forecast its future CAM generation times; then, the vehicle autonomously selects the radio resources for message broadcasting on the basis of the forecast provided by the algorithm. This action is combined with a wise analysis of the radio resources available for transmission, that identifies subchannels where collisions might occur, to avoid selecting them.</div><div>Extensive simulations show that the accuracy in the prediction of the CAMs’ temporal pattern is excellent. Exploiting this knowledge in the strategy for radio resource assignment, and carefully identifying idle resources, allows to outperform the legacy LTE-V2X Mode 4 in all respects.</div>

Machine Learning for Disseminating Cooperative Awareness Messages in Cellular V2V Communications

<div>This paper develops a novel Machine Learning (ML)-based strategy to distribute aperiodic Cooperative Awareness Messages (CAMs) through cellular Vehicle-to-Vehicle (V2V) communications. According to it, an ML algorithm is employed by each vehicle to forecast its future CAM generation times; then, the vehicle autonomously selects the radio resources for message broadcasting on the basis of the forecast provided by the algorithm. This action is combined with a wise analysis of the radio resources available for transmission, that identifies subchannels where collisions might occur, to avoid selecting them.</div><div>Extensive simulations show that the accuracy in the prediction of the CAMs’ temporal pattern is excellent. Exploiting this knowledge in the strategy for radio resource assignment, and carefully identifying idle resources, allows to outperform the legacy LTE-V2X Mode 4 in all respects.</div>

Optimization of the AODV-Based Packet Forwarding Mechanism for BLE Mesh Networks

The standard Bluetooth Low-Energy mesh networks assume the use of flooding for multihop communications. The flooding approach causes network overheads and delays due to continuous message broadcasting in the absence of a routing mechanism. Among the routing protocols, AODV is one of the most popular and robust routing protocol for wireless ad hoc networks. In this paper, we optimized the AODV protocol for Bluetooth Low-Energy communication to make it more efficient in comparison to the mesh protocol. With the proposed protocol (Optimized AODV (O-AODV)), we were able to achieve lower overheads, end-to-end delay, and average per-hop one-way delay in comparison to the BLE mesh (flooding) protocol and AODV protocol for all three scenarios (linear topology with ten nodes, multipath topology with six and ten nodes). In addition, the proposed protocol exhibited practically constant route requests and route reply setup times. Furthermore, the proposed protocol demonstrated a better Packet Delivery Ratio (PDR) for O-AODV (84%) in comparison to AODV (71%), but lower than the PDR of the mesh (flooding) protocol with 93%.

Secured Message Broadcasting in VANET using Blowfish Algorithm with Oppositional Deer Hunting Optimization

Emergency Message broadcasting is an important process in VANET. Security and reliable transmission are the two major concerns in message broadcasting. VANET is open to unauthorized nodes, hackers, misbehaving vehicles, malicious attackers etc without security. Without valid confirmation of authorized vehicles, these types of attacks may occur. To enhance the reliability in message broadcasting, some existing techniques are used. They transmit the data without much delay but they didn’t provide any trusted authentication. So hackers, malicious nodes, unauthorized vehicles may easily interrupt the emergency messages. Also Brute force attack, Man in Middle attack are not identified and eliminated. In this research, a trust based secured broadcasting mechanism is developed which ensures the metrics such as security, privacy, integrity, trust etc. The major intension of this research is to reduce latency and provide high reliable, secure and efficient communication over the vehicles. The data such as vehicle position, location, speed, and other traffic information’s are generated and stored in a separate table. A network is created with varying densities. A path is generated for message broadcasting between source and destination based on the specific gateway estimated. Here, Optimal Wireless Access in Vanet (OWAV) Protocol is employed to gather vehicle related information to reduce the delay. Blowfish encryption algorithm along with Oppositional Deer Hunting Optimization (ODHO) is used to store the trusted vehicles location to avoid unauthorized tracking. The performance of the proposed research is analyzed with various metrics such as Packet delivery ratio (PDR), transmission delay, encryption time, throughput, computational overhead etc. The efficiency of the research is compared with other existing methods.

Black Widow Optimization Algorithm and Similarity Index Based Adaptive Scheduled Partitioning Technique for Reliable Emergency Message Broadcasting in VANET

The vehicular ad hoc network (VANET) topology will change the mobility of the nodes and the data delivery will be efficient in the vehicle environment. This technique uses the density, mobility, dissemination in the requirements of emergency message broadcasting. The emergency message is broadcast on the road causes many issues like reliability, latency and scalability. Beacons are used in the VANET to broadcast messages and get the information from neighbours. When more vehicles transmit the messages in equal time lead a frequent broadcast storm the vehicles are faced the message delivery failure. Adaptive Scheduled Partitioning and Broadcasting technique (ASPBT) is used in our paper for message reliability, and the transmission efficiency will adjust the partitions and beacon automatically for reducing retransmissions. The partition size is determined using the density of network transmission of each partition schedule is estimated using the Black Widow Optimization (BWOA). The emergency message gets low delay and redundancy of the message is reducing, ASPBT include the forwarding of novel with the selection of optimal partition. The performance analysis is done with the existing methods for the determination of efficiency, redundancy, collision, and delay. The efficiency of proposed technique as 98% comparing with existing broadcast schemes of VANET.

Ciphertext-Only Attack on RSA Using Lattice Basis Reduction

We use lattice basis reduction for ciphertext-only attack on RSA. Our attack is applicable in the conditions when known attacks are not applicable, and, contrary to known attacks, it does not require prior knowledge of a part of a message or key, small encryption key, e, or message broadcasting. Our attack is successful when a vector, comprised of a message and its exponent, is likely to be the shortest in the lattice, and meets Minkowski's Second Theorem bound. We have conducted experiments for message, keys, and encryption/decryption keys with sizes from 40 to 8193 bits, with dozens of thousands of successful RSA cracks. It took about 45 seconds for cracking 2001 messages of 2050 bits and for large public key values related with Euler’s totient function, and the same order private keys. Based on our findings, for RSA not to be susceptible to the proposed attack, it is recommended avoiding RSA public key form used in our experiments