Modular Message Queue for Ocean of Things Bandwidth Optimization
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Solution Overview
Problem
In the Ocean of Things (OoT) environment, floating sensors collect large amounts of data at rates exceeding the limited communication bandwidth, making it challenging to transmit essential information efficiently due to restrictive data rate constraints.
Innovation Solution
A system utilizing a modular message structure with priority-based message packing and data packet queue management, where data packets are prioritized based on minimum reporting frequency and value optimization algorithms, ensuring that critical information is transmitted effectively over limited bandwidth links.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data collection rate is increased to capture more environmental information, then information completeness is improved, but transmission bandwidth requirement increases beyond available capacity
Solution Approach 1:
The patent segments data into discrete packets with priority levels, allowing selective transmission of critical information. Data packets are divided into different priority categories (e.g., highest priority for safety-critical data, lower priority for routine monitoring data), enabling the system to transmit essential information within bandwidth constraints while maintaining information completeness for critical parameters.
Solution Approach 2:
The patent applies different quality levels to different data packets based on their importance. Critical data packets receive higher priority and are transmitted with higher reliability and frequency, while less critical data packets are transmitted with lower priority. This local quality differentiation ensures that limited bandwidth is allocated to the most important information, preventing loss of critical data while managing overall data volume.
2Productivity
If traditional data management techniques are used under restrictive data rate constraints, then system simplicity is maintained, but transmission efficiency deteriorates
Solution Approach 1:
The patent implements preliminary actions by pre-classifying data packets into priority levels before transmission, pre-configuring quality requirements for different data types, and pre-establishing transmission schedules. This preliminary organization of data based on importance allows the system to efficiently manage limited bandwidth without complex real-time decision-making, improving transmission efficiency while keeping the data management framework structured and manageable.
Solution Approach 2:
The patent introduces dynamic elements to the data management system, including configurable priority levels that can be adjusted based on operational conditions, adaptive quality requirements that change with environmental factors, and flexible transmission parameters that respond to bandwidth availability. This dynamic approach allows the system to optimize transmission efficiency for different scenarios while maintaining a relatively simple base architecture.
3Loss of information
If all collected data is transmitted to ensure complete information delivery, then data completeness is improved, but bandwidth consumption increases beyond limited capacity
Solution Approach 1:
The patent extracts and transmits only the essential and critical information from the collected data set. By identifying and separating high-priority data packets (such as safety-critical measurements, alarm conditions, and key environmental parameters) from routine or low-value data, the system ensures complete delivery of important information while significantly reducing overall bandwidth consumption. Non-critical data is either transmitted with lower priority or filtered out entirely.
Data Source
AI summary
A system and method provide a combination of a modular message structure, a priority-based message packing scheme, and a data packet queue management system to optimize the information content of a transmitted message in, for example, the Ocean of Things (OoT) environment. The modular message structure starts with a header that provides critical information and reference points for time and location. The rest of the message is composed of modular data packets, each of which has a data ID section that the message decoder uses for reference when reconstructing the message contents, an optional size section that specifies the length of the following data section if it can contain data of variable length, and a data section that can be compressed in a manner unique to that data type. The message packing scheme uses a combination of priority level and minimum reporting interval, both of which are dynamically configurable for each data packet type, to maximize the value of the information contained in the modular data packets included in each message. Finally, the data packet queues manage temporary storage of data packets that have been generated but not yet included in an outgoing message.