Exploration and Design of High Performance Variation Tolerant On-Chip Interconnects

Siirretty Doriast

High-performance long NoC link using delay-insensitive current-mode signaling

High-performance long-range NoC link enables efficient implementation of network-on-chip topologies which inherently require high-performance long-distance point-to-point communication such as torus and fat-tree structures. In addition, the performance of other topologies, such as mesh, can be improved by using high-performance link between few selected remote nodes.We presented novel implementation of high-performance long-range NoC link based onmultilevel current-mode signaling and delayinsensitive two-phase 1-of-4 encoding. Current-mode signaling reduces the communication latency of long wires significantlycompared to voltage-mode signaling, making it possible to achieve high throughput without pipelining and/or using repeaters. The performance of the proposed multilevel current-mode interconnect is analyzed and compared with two reference voltage mode interconnects. These two reference interconnects are designed using two-phase 1-of-4 encoded voltage-mode signaling, one with pipeline stages and the other using optimal repeater insertion. The proposed multilevel current-mode interconnect achieves higher throughput and lower latency than the two reference interconnects. Its throughput at 8mm wire length is 1.222GWord/swhich is 1.58 and 1.89 times higher than the pipelined and optimal repeater insertion interconnects, respectively. Furthermore, its power consumption is less than the optimal repeater insertion voltage-mode interconnect, at 10mm wire length its power consumption is 0.75mW while the reference repeater insertion interconnect is 1.066 mW. The effect of crosstalk is analyzed using four-bit parallel data transfer with the best-case and worst-case switching patterns and a transmission line model which has both capacitive coupling and inductive coupling.</p

Quantum Key Distribution: Modeling and Simulation through BB84 Protocol Using Python3

Autonomous “Things” is becoming the future trend as the role, and responsibility of IoT keep diversifying. Its applicability and deployment need to re-stand technological advancement. The versatile security interaction between IoTs in human-to-machine and machine-to-machine must also endure mathematical and computational cryptographic attack intricacies. Quantum cryptography uses the laws of quantum mechanics to generate a secure key by manipulating light properties for secure end-to-end communication. We present a proof-of-principle via a communication architecture model and implementation to simulate these laws of nature. The model relies on the BB84 quantum key distribution (QKD) protocol with two scenarios, without and with the presence of an eavesdropper via the interception-resend attack model from a theoretical, methodological, and practical perspective. The proposed simulation initiates communication over a quantum channel for polarized photon transmission after a pre-agreed configuration over a Classic Channel with parameters. Simulation implementation results confirm that the presence of an eavesdropper is detectable during key generation due to Heisenberg’s uncertainty and no-cloning principles. An eavesdropper has a 0.5 probability of guessing transmission qubit and 0.25 for the polarization state. During simulation re-iterations, a base-mismatch process discarded about 50 percent of the total initial key bits with an Error threshold of 0.11 percent.</p

Hybrid Internal Anomaly Detection System for IoT: Reactive Nodes with Cross-Layer Operation

We present a hybrid internal anomaly detection system that shares detection tasks between router and nodes. It allows nodes to react instinctively against the anomaly node by enforcing temporary communication ban on it. Each node monitors its own neighbors and if abnormal behavior is detected, the node blocks the packets of the anomaly node at link layer and reports the incident to its parent node. A novel RPL control message, Distress Propagation Object (DPO), is formulated and used for reporting the anomaly and network activities to the parent node and subsequently to the router. The system has configurable profile settings and is able to learn and differentiate between the nodes normal and suspicious activities without a need for prior knowledge. It has different subsystems and operation phases that are distributed in both the nodes and router, which act on data link and network layers. The system uses network fingerprinting to be aware of changes in network topology and approximate threat locations without any assistance from a positioning subsystem. The developed system was evaluated using test-bed consisting of Zolertia nodes and in-house developed PandaBoard based gateway as well as emulation environment of Cooja. The evaluation revealed that the system has low energy consumption overhead and fast response. The system occupies 3.3 KB of ROM and 0.86 KB of RAM for its operations. Security analysis confirms nodes reaction against abnormal nodes and successful detection of packet flooding, selective forwarding, and clone attacks. The system’s false positive rate evaluation demonstrates that the proposed system exhibited 5% to 10% lower false positive rate compared to simple detection system

The 9th International Conference on Ambient Systems, Networks and Technologies (ANT 2018)

In this paper, we analyze the performance of the state-of-the-art end-to-end security schemes in healthcare Internet of Things (IoT) systems. We identify that the essential requirements of robust security solutions for healthcare IoT systems comprise of (i) low-latency secure key generation approach using patients’ Electrocardiogram (ECG) signals, (ii) secure and efficient authentication and authorization for healthcare IoT devices based on the certificate-based datagram Transport Layer Security (DTLS), and (iii) robust and secure mobility-enabled end-to-end communication based on DTLS session resumption. The performance of the state-of-the-art security solutions including our end-to-end security scheme is tested by developing a prototype healthcare IoT system. The prototype is built of a Pandaboard, a TI SmartRF06 board and WiSMotes. The Pandaboard along with the CC2538 module acts as a smart gateway and the WisMotes act as medical sensor nodes. Based on the analysis, we found out that our solution has the most extensive set of performance features in comparison to related approaches found in the literature. The performance evaluation results show that compared to the existing approaches, the cryptographic key generation approach proposed in our end-to-end security scheme is on average 1.8 times faster than existing key generation approaches while being more energy-efficient. In addition, the scheme reduces the communication overhead by 26% and the communication latency between smart gateways and end users by 16%. Our scheme is also approximately 97% faster than certificate based and 10% faster that symmetric key-based DTLS. Certificate based DTLS requires about 2.9 times more ROM and 2.2 times more RAM resources. On the other hand, the ROM and RAM requirements of our scheme are almost as low as in symmetric key-based DTLS.</p

The 11th International Conference on Emerging Ubiquitous Systems and Pervasive Networks ( EUSPN 2020)

The potential of IoT in contributing towards sustainable economic development in Sub-Saharan Africa (SSA) through digital transformation and effective service delivery is widely accepted. However, the unreliability/unavailability of connectivity and power grid infrastructure as well as the unaffordability of the overall system hinders the implementation of a multi-layered IoT architecture for rural societal services in SSA. In this work, affordable IoT architecture that operates without reliance on broadband connectivity and power grid is developed. The architecture employs energy harvesting system and performs data processing, actuation decisions and network management locally by integrating a customized low-cost computationally capable device with the gateway. The sharing of this device among the water resource and quality management, healthcare and agriculture applications further reduces the overall system cost. The evaluation of LPWAN technologies reveals that LoRaWAN has lower cost with added benefits of adaptive data rate and largest community support while providing comparable performance and communication range with the other technologies. The relevant results of the analysis is communicated to end-users’ mobile device via 2G/3G GPRS. Hence, the proposed IoT architecture enables the implementation of IoT systems for improving efficiency in three key application areas at low cost.</p

Real-Time Classification of Pain Level Using Zygomaticus and Corrugator EMG Features

The real-time recognition of pain level is required to perform an accurate pain assessment of patients in the intensive care unit, infants, and other subjects who may not be able to communicate verbally or even express the sensation of pain. Facial expression is a key pain-related behavior that may unlock the answer to an objective pain measurement tool. In this work, a machine learning-based pain level classification system using data collected from facial electromyograms (EMG) is presented. The dataset was acquired from part of the BioVid Heat Pain database to evaluate facial expression from an EMG corrugator and EMG zygomaticus and an EMG signal processing and data analysis flow is adapted for continuous pain estimation. The extracted pain-associated facial electromyography (fEMG) features classification is performed by K-nearest neighbor (KNN) by choosing the value of k which depends on the nonlinear models. The presentation of the accuracy estimation is performed, and considerable growth in classification accuracy is noticed when the subject matter from the features is omitted from the analysis. The ML algorithm for the classification of the amount of pain experienced by patients could deliver valuable evidence for health care providers and aid treatment assessment. The proposed classification algorithm has achieved a 99.4% accuracy for classifying the pain tolerance level from the baseline (P0 versus P4) without the influence of a subject bias. Moreover, the result on the classification accuracy clearly shows the relevance of the proposed approach.</p

The 11th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2020)

 Ensuring food security has become a challenge in Sub-Saharan Africa (SSA) due to combined effects of climate change, high population growth, and relying on rainfed farming. Governments are establishing shared irrigation infrastructure for smallholder farmers as part of the solutions for food security. However, the irrigated farms often failed to achieve the expected crop yield. This is partly due to lack of water management system in the irrigation infrastructure. In this work, IoT-based irrigation management system is proposed after investigating problems of irrigated farmlands in three SSA countries, Ethiopia, Kenya, and South Africa as case studies. Resource-efficient IoT architecture is developed that monitors soil, microclimate and water parameters and performs appropriate irrigation management. Indigenous farming and expert knowledge, regional weather information, crop and soil specific characteristics are also provided to the system for informed-decision making and efficient operation of the irrigation management system. In SSA, broadband connectivity and cloud services are either unavailable or expensive. To tackle these limitations, data processing, network management and irrigation decisions and communication to the farmers are carried out locally, without the involvement of any back-end servers. Furthermore, the use of green energy sources and resource-aware intelligent data analysis algorithm is studied. The intelligent data analysis helps to discover new knowledge that support further development of agricultural expert knowledge. The proposed IoT-based irrigation management system is expected to contribute towards long term and sustainable high crop yield with minimum resource consumption and impact to the biodiversity around the case farmlands.</p

Performance of three multi-species rapid diagnostic tests for diagnosis of Plasmodium falciparum and Plasmodium vivax malaria in Oromia Regional State, Ethiopia

BACKGROUND: Malaria transmission in Ethiopia is unstable and variable, caused by both Plasmodium falciparum and Plasmodium vivax. The Federal Ministry of Health (FMoH) is scaling up parasitological diagnosis of malaria at all levels of the health system; at peripheral health facilities this will be through use of rapid diagnostic tests (RDTs). The present study compared three RDT products to provide the FMoH with evidence to guide appropriate product selection. METHODS: Performance of three multi-species (pf-HRP2/pan-pLDH and pf-HRP2/aldolase) RDTs (CareStart, ParaScreen and ICT Combo) was compared with 'gold standard' microscopy at three health centres in Jimma zone, Oromia Regional State. Ease of RDT use by health extension workers was assessed at community health posts. RDT heat stability was tested in a controlled laboratory setting according to WHO procedures. RESULTS: A total of 2,383 patients with suspected malaria were enrolled between May and July 2009, 23.2% of whom were found to be infected with Plasmodium parasites by microscopy. All three RDTs were equally sensitive in detecting P. falciparum or mixed infection: 85.6% (95% confidence interval 81.2-89.4). RDT specificity was similar for detection of P. falciparum or mixed infection at around 92%. For detecting P. vivax infection, all three RDTs had similar sensitivity in the range of 82.5 to 85.0%. CareStart had higher specificity in detecting P. vivax (97.2%) than both ParaScreen and ICT Combo (p < 0.001 and p = 0.05, respectively). Health extension workers preferred CareStart and ParaScreen to ICT Combo due to the clear labelling of bands on the cassette, while the 'lab in a pack' style of CareStart was the preferred design. ParaScreen and CareStart passed all heat stability testing, while ICT Combo did not perform as well. CONCLUSIONS: CareStart appeared to be the most appropriate option for use at health posts in Ethiopia, considering the combination of quantitative performance, ease of use and heat stability. When new products become available, the choice of multi-species RDT for Ethiopia should be regularly re-evaluated, as it would be desirable to identify a test with higher sensitivity than the ones evaluated here