Connectivity is at the heart of the future Internet-of-Things (IoT) infrastructure, which can control and communicate with remote sensors and actuators for the beacons, data collections, and forwarding nodes. Existing sensor network solutions cannot solve the bottleneck problems near the sink node; the tree-based Internet architecture has the single point of failure. To solve current deficiencies in multi-hop mesh network and cross-domain network design, we propose a mesh inside a mesh IoT network architecture. Our designed "edge router" incorporates these two mesh networks together and performs seamlessly transmission of multi-standard packets. The proposed IoT testbed interoperates with existing multi-standards (Wi-Fi, 6LoWPAN) and segments of networks, and provides both high-throughput Internet and resilient sensor coverage throughout the community.
Voluntary Data Preservation Mechanism in Base Station-less Sensor Networks
We consider the problem of preserving a large amount of data generated inside base station-less sensor networks, when sensor nodes are controlled by different authorities and behave selfishly. We modify the VCG mechanism to guarantee that each node, including the source nodes with overflow data packets, will voluntarily participate in data preservation. The mechanism ensures that each node truthfully reports its private type and network achieves efficiency for all the preserved data packets. Extensive simulations are conducted to further validate our results.
- Award ID(s):
- 2131309
- Publication Date:
- NSF-PAR ID:
- 10357766
- Journal Name:
- 12th EAI International Conference on Game Theory for Networks (GameNets 2022).
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
A Mobile Ad-hoc Network (MANET) is a collection of nodes that communicate with each other wirelessly without any central support or conventional structure. The transmission of data packets over wireless channels in MANETs helps to maintain communication. Ad-hoc On-Demand Distance Vector Routing is a reactive routing protocol associated with MANET which creates a route to destination by broadcasting route request packets through the entire network. A link failure in this type of protocol causes the source to flood the network with these Route Request packets that leads to congestion in the network and performance degradation. This paper proposes an Efficient Multipath AODV routing algorithm that determines if a node in a network is relaying or is silent in the process of route discovery to send data packets from the source to destination. Simulation results show the proposed routing algorithm controls congestion and enhances performance in the network as not all network nodes have to participate in the route discovery for a particular source-destination pair.
-
We present the first all-optical network, Baldur, to enable power-efficient and high-speed communications in future exascale computing systems. The essence of Baldur is its ability to perform packet routing on-the-fly in the optical domain using an emerging technology called the transistor laser (TL), which presents interesting opportunities and challenges at the system level. Optical packet switching readily eliminates many inefficiencies associated with the crossings between optical and electrical domains. However, TL gates consume high power at the current technology node, which makes TL-based buffering and optical clock recovery impractical. Consequently, we must adopt novel (bufferless and clock-less) architecture and design approaches that are substantially different from those used in current networks. At the architecture level, we support a bufferless design by turning to techniques that have fallen out of favor for current networks. Baldur uses a low-radix, multi-stage network with a simple routing algorithm that drops packets to handle congestion, and we further incorporate path multiplicity and randomness to minimize packet drops. This design also minimizes the number of TL gates needed in each switch. At the logic design level, a non-conventional, length-based data encoding scheme is used to eliminate the need for clock recovery. We thoroughly validate and evaluatemore »
-
A practical WiFi system only achieves a discrete data rate adjustment due to hardware constraints while channel signal-to-noise ratio (SNR) is continuous. This mismatch leads to the SNR gaps. In this paper, we introduce a novel communication mechanism, CoS (Communication through Silent subcarriers), which turns the wasted SNR gaps into new opportunities for transmitting control messages for free. Compared with traditional piggybacking schemes, CoS is more reliable to transmit control messages from one node to many nodes. In CoS, silent subcarriers are inserted into data packets and the intervals between adjacent silent subcarriers are utilized to encode information. Since the wasted SNR gap results in under-utilization of the channel code, the data bit errors induced by silent subcarriers are corrected by the correcting capability of the existing channel code as long as we carefully design the total number of inserted silent subcarriers. Based on CoS, we design CoS-MAC to validate the effectiveness of CoS. We measure the throughput of free control messages achieved by CoS under various channel conditions and conduct simulations to show the throughput gain achieved by CoS-MAC over the existing schemes.
-
There is an increasing demand for performing machine learning tasks, such as human activity recognition (HAR) on emerging ultra-low-power internet of things (IoT) platforms. Recent works show substantial efficiency boosts from performing inference tasks directly on the IoT nodes rather than merely transmitting raw sensor data. However, the computation and power demands of deep neural network (DNN) based inference pose significant challenges when executed on the nodes of an energy-harvesting wireless sensor network (EH-WSN). Moreover, managing inferences requiring responses from multiple energy-harvesting nodes imposes challenges at the system level in addition to the constraints at each node. This paper presents a novel scheduling policy along with an adaptive ensemble learner to efficiently perform HAR on a distributed energy-harvesting body area network. Our proposed policy, Origin, strategically ensures efficient and accurate individual inference execution at each sensor node by using a novel activity-aware scheduling approach. It also leverages the continuous nature of human activity when coordinating and aggregating results from all the sensor nodes to improve final classification accuracy. Further, Origin proposes an adaptive ensemble learner to personalize the optimizations based on each individual user. Experimental results using two different HAR data-sets show Origin, while running on harvested energy, to bemore »
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Publisher's Version of Record
- The DOI is not currently available
