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We propose a family of location-based load balancing muting algorithms for wireless sensor networks (WSNs) called COBRA. In this approach, we combine local load balancing with shortest path routing to strike a balance between hop-count efficiency and load distribution. COBRA's advantages over traditional routing protocols are: (i) a significant reduction of hot-spot occurrences (i. e., nodes or areas of high congestion level), thus enabling longer uninterrupted operation of WSNs, (ii) a light-weight and scalable implementation that requires only local congestion updates, ideal for implementation on computationally challenged platforms, and (iii) combination of routing and congestion avoidance tasks in the protocol stack-a feature that leads to smoother TCP operation over wireless channels with fewer false positives on existing congestion and subsequent sending rate reduction by TCP. We show through simulation that COBRA's local load sensing in combination with a shortest path routing component is a promising paradigm that improves global performance in terms of throughput and scalability, while matching other protocols in the traditional energy efficiency objective.