Context-aware Communication Research Articles

Deep learning-powered visual place recognition for enhanced mobile multimedia communication in autonomous transport systems

The progress of autonomous transport systems (ATS) involves efficient multimedia communication for real-time data tradeoffs and environmental issues. Deep learning (DL) powered visual place recognition (VPR) was developed as an effective tool to improve mobile multimedia communication in ATS. VPR relates to the capability of a method or device to recognize and identify particular places or locations from the visual scene. This procedure involves inspecting visual data, like images or video frames, to control the unique features or features connected with diverse locations. By leveraging camera sensors, VPR allows vehicles to detect their surroundings, enabling context-aware communication and enhancing the entire system's performance. DL-empowered VPR offers a transformative manner to improve mobile multimedia communication in ATS. By identifying and understanding their situation, autonomous vehicles can communicate most effectively and operate reliably and safely, paving the way for a future characterized by seamless and intelligent transportation. This article develops a novel Deep Learning-Powered Visual Place Recognition for Enhanced Multimedia Communication in Autonomous Transport Systems (DLVPR-MCATS) methodology. The main aim of the DLVPR-MCATS methodology is to recognize visual places or not utilize optimal DL approaches. For this purpose, the DLVPR-MCATS approach utilizes a bilateral filtering (BF) based preprocessing model. For the feature fusion model, the DLVPR-MCATS approach follows three models: residual network (ResNet), EfficientNet, and MobileNetv2. Moreover, the hyperparameter tuning method uses the Harris Hawks Optimization (HHO) model. Finally, the bidirectional long short-term memory (BiLSTM) technique is implemented to recognize visual places. A wide range of simulations is executed to validate the solution of the DLVPR-MCATS method. The experimental validation of the DLVPR-MCATS method portrayed a superior performance over other models concerning various aspects.

HVTSurv: Hierarchical Vision Transformer for Patient-Level Survival Prediction from Whole Slide Image

Survival prediction based on whole slide images (WSIs) is a challenging task for patient-level multiple instance learning (MIL). Due to the vast amount of data for a patient (one or multiple gigapixels WSIs) and the irregularly shaped property of WSI, it is difficult to fully explore spatial, contextual, and hierarchical interaction in the patient-level bag. Many studies adopt random sampling pre-processing strategy and WSI-level aggregation models, which inevitably lose critical prognostic information in the patient-level bag. In this work, we propose a hierarchical vision Transformer framework named HVTSurv, which can encode the local-level relative spatial information, strengthen WSI-level context-aware communication, and establish patient-level hierarchical interaction. Firstly, we design a feature pre-processing strategy, including feature rearrangement and random window masking. Then, we devise three layers to progressively obtain patient-level representation, including a local-level interaction layer adopting Manhattan distance, a WSI-level interaction layer employing spatial shuffle, and a patient-level interaction layer using attention pooling. Moreover, the design of hierarchical network helps the model become more computationally efficient. Finally, we validate HVTSurv with 3,104 patients and 3,752 WSIs across 6 cancer types from The Cancer Genome Atlas (TCGA). The average C-Index is 2.50-11.30% higher than all the prior weakly supervised methods over 6 TCGA datasets. Ablation study and attention visualization further verify the superiority of the proposed HVTSurv. Implementation is available at: https://github.com/szc19990412/HVTSurv.

Exploring Opportunities to Improve Physical Activity in Individuals with Spinal Cord Injury Using Context-Aware Messaging

Spinal cord injury (SCI) affects the mobility of 250,000 people per year worldwide. Physical activity (PA) in individuals with SCI is positively associated with improved mental and physical health outcomes. Mobile technologies have been developed to motivate individuals with SCI to increase PA using activity tracking and real-time feedback. We conducted semi-structured interviews and participatory design sessions with 15 manual wheelchair users with SCI and eight of their family members/friends to investigate user impressions of future technologies that might use computer-mediated, sensor-triggered communication to motivate PA. We assessed barriers to PA and how context-aware communication could help overcome them. Participants with SCI expressed that PA tracking and communication technologies must be tailored to their specific needs. Further analysis revealed that context-aware messaging could help participants with SCI connect with others to initiate timely conversations about overcoming PA barriers, and to provide encouragement to meet their PA goals. We discuss opportunities to empower individuals with SCI with regards to PA using tailored, context-aware communication.

CACS: A Context-Aware and Anonymous Communication Framework for an Enterprise Network Using SDN

The emergence of software-defined networking (SDN) has revolutionized the management of an enterprise network. The SDN-based design provides flexibility in network management, which spans over multiple applications, e.g., routing, switching, forwarding, and controlling. It reduces the reliance on vendor-specific devices and middlebox solutions, such as firewalls, intrusion detection systems (IDSs), intrusion prevention systems (IPSs), etc. Furthermore, due to the integration of different technologies, privacy is one of the core issues faced by the enterprise. Host anonymity is one of the techniques to safeguard against privacy attacks; however, the existing anonymization solutions provide better anonymity, but at the cost of higher latency and are most suited for Internet traffic. To tackle this issue in an enterprise network, we propose an SDN-based communication framework using enterprise integration patterns (EIPs) that offers anonymous communication in an enterprise environment. Host anonymity is achieved by replacing the real IP address with the spoofed IP address during the transmission of data packets inside the network. Unlike the traditional networks, SDN can modify the header fields of packets as they traverse in the network from the source to the destination. In addition to the host anonymity, this framework also provides context-aware communication by leveraging the SDN global visibility characteristic, where application services are discoverable on the network without disclosing the addresses of the application servers. Moreover, context-aware services enable network traffic to be routed based on the application-layer services rather than the network-layer information. In the end, evaluation of the proposed framework is carried out with respect to the performance of anonymous communication, computational complexity, and security of the complete proposed framework. In addition, we also highlighted that the proposed framework is more suitable for heterogeneous network environments such as Internet of Things-based solutions.

Context-Aware Content Selection and Message Generation for Collective Perception Services

Collective perception messages (CPMs) inform neighbors about detected objects and their current status. Although CPMs can greatly contribute to improving vehicle perception, their performance will degrade if the wireless channel is saturated and/or vehicles must process excessively high amount of data to build such a perception. Channel saturation and processing overhead can be induced by transmissions of CPMs if vehicles and roadside infrastructure transmit CPMs too often with too much redundant information. Indeed, according to the current draft standard, the CPM generation frequency at individual vehicles and infrastructure can be as high as 10 Hz and depending on the perception capability, individual CPMs can be quite heavy (around 1500 Bytes), containing redundant information. It is hence important to integrate techniques that reduce information redundancy while providing sufficient perception with optimal resource use. In this paper, we propose context-aware communication schemes that control CPM content selection and transmission. Two types of contexts, particularly radio resource use (channel busy ratio: CBR) and infrastructure availability, have been considered in the proposed schemes. Using a network simulator, we evaluated the performances of the proposed schemes in terms of CBR, packet delivery ratio and awareness ratio. The simulation results show that the scheme that takes into account both resource use and infrastructure availability offers the best performance on all the above metrics.

An Optimal Approach to Enhance Context Aware Description Administration Service for Cloud Robots in a Deep Learning Environment

As the advancements in the field of artificial intelligence technologies continue to grow, robots are being built by the researchers as an attempt to render services to the people. In this regard, the robots can communicate effectively with the people and be able to complete all the tasks adequately given to them. These service robots while being developed requires the dialogue services to be developed to interact effectively with human beings providing far better user experience. Thus, the robot been built can provide domain-specific knowledge as well as able to provide consultations in various domains. We in this paper adopted a service-oriented approach for developing context-aware communication services for the cloud robot. The proposed work aims at training the context-aware model developed. The context-aware model is responsible for answering the questions put forward by the users and possess the ability to exploit the answers corresponding to the questions presented. An integrated framework is used to combine the contextual information and communication services. The performance of the proposed model can be evaluated based on Inverse Rank Mean (IRM). Evolutionary testing methods are used for testing the data in the proposed model. The results thus obtained shows the effectiveness of the proposed approach.

Migration of existing software systems to mobile computing platforms: a systematic mapping study

Mobile computing has fast emerged as a pervasive technology to replace the old computing paradigms with portable computation and context-aware communication. Existing software systems can be migrated (while preserving their data and logic) to mobile computing platforms that support portability, context-sensitivity, and enhanced usability. In recent years, some research and development efforts have focused on a systematic migration of existing software systems to mobile computing platforms. To investigate the research state-of-the-art on the migration of existing software systems to mobile computing platforms. We aim to analyze the progression and impacts of existing research, highlight challenges and solutions that reflect dimensions of emerging and futuristic research. We followed evidence-based software engineering (EBSE) method to conduct a systematic mapping study (SMS) of the existing research that has progressed over more than a decade (25 studies published from 1996–2017). We have derived a taxonomical classification and a holistic mapping of the existing research to investigate its progress, impacts, and potential areas of futuristic research and development. The SMS has identified three types of migration namely Static, Dynamic, and State-based Migration of existing software systems to mobile computing platforms. Migration to mobile computing platforms enables existing software systems to achieve portability, context-sensitivity,and high connectivity. However, mobile systems may face some challenges such as resource poverty, data security, and privacy. The emerging and futuristic research aims to support patterns and tool support to automate the migration process. The results of this SMS can benefit researchers and practitioners-by highlighting challenges, solutions, and tools, etc., -to conceptualize the state-of-the-art and futuristic trends that support migration of existing software to mobile computing.

A context-aware mobile application framework using audio watermarking

In this paper, we propose a proximity-based indoor positioning system which is capable of monitoring mobile device user’s indoor locations where the commonly used GPS signal is unavailable or weak. The designed system is aimed to be integrated into a context-aware communications system to prevent transmission of irrelevant content to all users but easing delivery of the location-based information. Similar to the beacon technology that assigns a code to each targeted position in an indoor location, our system labels the locations with audio watermark codes where user’s mobile device monitors and receives the watermarked audio. The proposed encoder performs code-division multiplexing that allows insertion of several location indexes into the same audio file. Watermark embedded through spread spectrum improves robustness to noise and guarantees a satisfactory performance even though the mobile device has a low band microphone. The designed decoder installs synchronization between the mobile device and the watermarked audio emitter in real time, and extracts the embedded watermark code words assigned to specific indoor locations. This invokes the context-aware content delivery module and the delivery is initiated. Position displacements of the mobile users are estimated by the time-of-flight technique and the users moving within the coverage range of the emitters are continuously monitored. Decoding is achieved in real time that enables the mobile users to reach to content delivered from different emitters within their coverage range. Performance tests demonstrate that the developed system enables to estimate the user position within the 7-m distance from the emitter while keeping inaudibility. We reached 2-m spatial resolution in discrimination of different emitters. The proposed framework can be considered as a promising alternative to latest technologies, i.e., Wi-Fi-based fingerprinting systems or beacons.

Adaptive Security for Self-Protection of Mobile Computing Devices

Mobile computing has emerged as a pervasive technology that empowers its users with portable computation and context-aware communication. Smart systems and infrastructures can exploit portable and context-aware computing technologies to provide any time, any place digitized services on the go. Despite the offered benefits, such as portability, context-sensitivity, and high connectivity, mobile computing also faces some critical challenges. These challenges include resource poverty as well as data security and privacy that need to be addressed to increase the pervasiveness of mobile systems. We propose to provide a self-protection mechanism for mobile devices against the unforeseen security threats that can attack the critical resources of mobile devices. We have unified the concepts of autonomic computing and computer security to develop a framework that enables adaptive security to dynamically configure the security measures of a mobile device. We have developed a framework - an android-based prototype - that supports automation and user decision to protect the critical hardware and software resources of a device. Evaluation results demonstrate (i) framework’s accuracy for runtime detection and minimization of threats, and (ii) framework’s efficiency for device’s resource utilization.

Integrating Licensed and Unlicensed Spectrum in the Internet of Vehicles with Mobile Edge Computing

In order to satisfy the application requirements in Internet of Vehicles scenarios, it is important to efficiently utilize different wireless spectrums while considering the dynamic features of network environments. In this article, we propose a context-aware communication approach to efficiently integrate different licensed and unlicensed spectrums leveraging the edge computing technologies. In addition, a joint aggregation, caching, and decentralization scheme is proposed to efficiently combine route aggregation, data caching, and decentralized computing approaches to compensate for the limited wireless resources. Asynchronous multihop broadcast and asynchronous multihop unicast schemes are introduced to improve the routing performance in multihop broadcast and multihop unicast communications, respectively. We conduct computer simulations to evaluate the effects of the proposed scheme by comparing it with other baseline approaches.

Formal Analysis of Language-Based Android Security Using Theorem Proving Approach

Mobile devices are an indispensable part of modern-day lives to support portable computations and context-aware communication. Android applications within a mobile device share data to support application operations and better user experience, which also increases security risks to device’s data integrity and confidentiality. To analyze the security provided by the Android permissions, modern security techniques, based on the programming languages, have been used to enforce best practices for developing the secure Android applications. Android security assessment, based on the language-based techniques in an informal setting without formal tool support, is tedious and error-prone. Furthermore, the lack of proof of the soundness of the language-based techniques raises questions about the validity of the analysis. To enable computer-aided formal verification in Android security domain, we have developed a mathematical model of language-based Android security using computer-based proof assistant Coq. One of the main challenges for mechanizing the language-based security in theorem prover relates to the complexity of variable bindings in language-based security techniques. As the main contributions of the paper: 1) the language-based security, including variable binding, is formalized in theorem prover Coq; 2) a formal type checker is built to type check (capture safe data flows within) Android applications using computer; and 3) the soundness of the language-based security technique (type system) is mechanically verified. The formal model of the Android type system and their proof of soundness are machine-readable, and their correctness can be checked in the computer using Coq proof and type checkers.

Towards Security as a Service to Protect the Critical Resources of Mobile Computing Devices

Mobile computing is fast replacing the traditional computing paradigms by offering its users to exploit portable computations and context-aware communications. Despite the benefits of mobile computing, such as portability and context-sensitivity, there are some critical challenges, such as resource poverty of mobile devices and security of mobile user’s data that must be addressed. Implementing the security mechanisms to execute on mobile devices can be challenging as mobile devices lack the required processor, memory and battery resources to support continuous and long-term execution of computation intensive tasks. Cloud computing model can provide virtually unlimited hardware, software, and service resources to compensate for the resource poverty of mobile devices. In recent years, there is a lot of research and development of solutions and frameworks that preserve the security and privacy of mobile devices and their data. However, there has been little effort to secure mobile devices while also supporting an efficient utilization of the limited resources available on mobile devices. In this paper, we propose Security as a Service for mobile devices (SeaaS for mobile) that integrates mobile computing and cloud computing technologies to secure the critical resources of mobile devices. The proposed solution aims to support 1) security for the data critical resources of mobile devices, and 2) security as a service by cloud servers for an efficient utilization of the mobile device resources. We demonstrate the security as a service based on a practical scenario for the security of mobile devices. The evaluation results show that the proposed solution is 1) accurate to detect the potential security threats, and is 2) computationally efficient for mobile devices. The proposed solution as part of ongoing research provides the foundations to develop a framework to address SeaaS for mobile. The proposed solution aims to advance the research state-of-the-art on software engineering, mobile cloud computing, while it specifically focuses exploiting cloud-based services to secure mobile devices.

CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks

CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks

CACA-UAN: A Context-Aware Communication Approach to Efficient and Reliable Underwater Acoustic Sensor Networks

Underwater acoustic sensor networks (UANs) have emerged as a promising technology recently, which can be applied in many areas such as military and civil, where the communication between devices is crucial and challenging owing to the unique characteristics of underwater acoustic-based environment, such as high latency and low bandwidth. In this paper, context awareness is applied to the design of an underwater communication approach, called context-aware communication approach for a UAN (CACA-UAN), which aims to improve the overall performance of the underwater communication. According to the results, the proposed CACA-UAN can increase the efficiency and reliability of the underwater communication system.

Context-aware wireless mobile autonomic computing and communications: research trends and emerging applications

Growing attention has recently been devoted to context-aware computing and communication systems, in particular concerning their evolution toward the new paradigm of context-aware autonomic computing and communications. Indeed, context awareness and autonomicity appear to be the indispensable glue technologies to accomplish efficient integration of modern software-intensive cyber-physical systems, operating in open and non-deterministic environments, and to master their complexity. This article provides an update on the latest developments in this field. Proposed methodologies and techniques are discussed and framed in the overall research problem. Moreover, future trends and research challenges are outlined by relating the basic concepts of context-aware autonomic computing and communications to the emerging paradigm of the self-aware Internet of Things, applications of which appear to be very promising examples of next-generation computing and communication systems.

Context and Network Aware Communication Strategies for Connected Vehicle Safety Applications

Connected vehicle systems, such as cooperative collision warning (CCW) or avoidance (CCA) systems, rely on vehicle-to-vehicle communication for obtaining real-time situational awareness and detecting possible hazards. The majority of systems that use vehicular networks may benefit from separation of functionalities in communication and application layers. This separation streamlines design of many applications and provides Internet-style flexibility. However, for critical applications, the inherent loss of performance due to independent operation of communication and application layers may result in unacceptable degradation of reliability. We show that by considering the context and network performance in the communication subsystem design (thus weakening layer independence), significant gain in system reliability is possible. Context awareness is achieved by coupling communication behavior to safety system performance; for example using vehicle tracking accuracy to determine the required communication timing. Network awareness is achieved by using feedback from the network to influence the estimated system performance (tracking error), and consequently the communication controller. Safety performance metrics that can be used include hazard detection accuracy, or warning accuracy for CCW, or vehicle tracking accuracy. Simulation results, using data from field tests, show the effectiveness of context and network aware communication.

A Case Study on the Estimation of the Amount of Harvested Agricultural Products through a Sensor Network

This study examined the predictability of harvested amounts of agricultural products by using the technology of a sensor network. For the prediction of harvested amounts of agricultural products in a fruit farm, the containers made for exclusive transportation of agricultural products were equipped with context aware sensor tags and a context aware communication module was implemented. The implemented system was installed on-site at the fruit farm to examine the data of the amount of harvested agricultural products carried by the containers from the farm to each storage location to provide the methods to predict the harvested amount of agricultural products. Results obtained from the empirical experiment showed the recognition of contents in each container. Reliability of communication between sensors and communication unit were essential for the prediction of harvested amount of agricultural products.

Cross-Layer Analysis in Cognitive Radio—Context Identification and Decision Making Aspects

Research on context-aware communications has recently led to the introduction of features and algorithms relying on the presence of rich, accurate context information, and requiring however, the introduction of cross-layer information exchanges. Cognitive radio (CR), in particular, is expected to benefit from context awareness, as the cognitive engine (CE) relies on the availability of multiple information sources to operate efficiently. In this context, this work delivers a detailed, yet concise classification and description of the information exchanged in a CR network between the layers of a generic protocol stack, and between each layer and the CE. For each layer, the key services provided and delivered are presented, followed by a catalogue of exchanged parameters. The analysis, supported by a set of use cases providing a quantitative assessment of the impact of cross-layer information exchanges in a CR framework, is the basis for the discussion of key implementation challenges and the identification of the most promising partition of functions and tasks between layers and CE.

Two-Level Software Architecture for Context-Aware Mobile Distributed Systems

Currently, there is a trend to develop context-aware mobile distributed systems (MDS), such as systems that recommend places according to the location and the path of users. Some of the key challenges in the development of this type of systems are the following: acquisition, management and use of data context. In this paper, we propose two-level software architecture to obtain, use and provide context information in a MDS. From our point of view, the proposed architecture takes into account the requirements that emerge from data collection, use and management of context, as well as the own features of MDS. Based on our software architecture, a context-aware group communication system is implemented, which allows members to have four types of context: physical activity, logical activity, location and level of sound.

A context-aware medical instant message middleware

Communication or the lack of it has been complained to be a major contributor to medical errors in healthcare. To enhance communication in hospital, diverse communication mechanisms are proposed. However, human directed communication in a complex clinical setting in which many people play diverse roles and need to collaborate in many parallel tasks is always in chaos and inefficient. Context-aware communication which can help target who should be communicated and what information should be provided for different scenarios has the potential to improve the communication in hospital. This paper proposes a flexible, automated and asynchronous context-aware medical instant message (IM) middleware which support dispatch, forward and routing different message to the right person in the right time based on the context information. A prototype of this IM communication middleware was implemented in real clinical setting for evaluation. The preliminary results demonstrate its novel features and clinical feasibility.